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Schlichte L, Setji N, Walter J, Acker Y, Casarett D, Pollak KI, Steinhauser K, Check DK, Lakis K, Schmid L, Ma JE. The Use of Templates for Documenting Advance Care Planning Conversations: A Descriptive Analysis. J Pain Symptom Manage 2023; 66:123-136. [PMID: 37080478 DOI: 10.1016/j.jpainsymman.2023.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 04/09/2023] [Accepted: 04/12/2023] [Indexed: 04/22/2023]
Abstract
CONTEXT While professional societies and expert panels have recommended quality indicators related to advance care planning (ACP) documentation, including using structured documentation templates, it is unclear how clinicians document these conversations. OBJECTIVE To explore how clinicians document ACP, specifically, which components of these conversations are documented. METHODS A codebook was developed based on existing frameworks for ACP conversations and documentation. ACP documentation from a hospital medicine quality improvement project conducted from November 2019 to April 2021 were included and assessed. Documentation was examined for the presence or absence of each component within the coding schema. Clinician documented ACP using three different note types: template (only template prompts were used), template plus (authors added additional text to the template), and free text only. ACP note components were analyzed by note type and author department. RESULTS A total of 182 ACP notes were identified and reviewed. The most common note type was template plus (58%), followed by free text (28%) and template (14%). The most frequent components across all note types were: important relationships to patient (92%), and discussion of life-sustaining treatment preferences (87%). There was considerable heterogeneity in the components across note types. The presence of components focused on treatment decisions and legal paperwork differed significantly between note types (P < 0.05). Components on preference for medical information, emotional state, or spiritual support were rarely included across all note types. CONCLUSION This study provides a preliminary exploration of ACP documentation and found that templates may influence what information is documented after an ACP conversation.
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Affiliation(s)
- Lindsay Schlichte
- Duke University School of Medicine (L.S.), Durham, North Carolina, USA
| | - Noppon Setji
- Division of General Internal Medicine, Department of Medicine (N.S., J.W., D.C., K.S., J.M.), Duke University School of Medicine, Durham, North Carolina, USA
| | - Jonathan Walter
- Division of General Internal Medicine, Department of Medicine (N.S., J.W., D.C., K.S., J.M.), Duke University School of Medicine, Durham, North Carolina, USA
| | - Yvonne Acker
- Patient Safety and Quality, Duke University Health System (Y.A.), Durham, North Carolina, USA
| | - David Casarett
- Division of General Internal Medicine, Department of Medicine (N.S., J.W., D.C., K.S., J.M.), Duke University School of Medicine, Durham, North Carolina, USA
| | - Kathryn I Pollak
- Department of Population Health Sciences (K.I.P., K.S., D.K.C.), Duke University, Durham, North Carolina, USA; Cancer Prevention and Control (K.I.P., K.S.), Duke Cancer Institute, Durham, North Carolina, USA; Department of Family Medicine and Community Health (K.I.P.), Duke University School of Medicine, Durham, North Carolina, USA
| | - Karen Steinhauser
- Division of General Internal Medicine, Department of Medicine (N.S., J.W., D.C., K.S., J.M.), Duke University School of Medicine, Durham, North Carolina, USA; Department of Population Health Sciences (K.I.P., K.S., D.K.C.), Duke University, Durham, North Carolina, USA; Cancer Prevention and Control (K.I.P., K.S.), Duke Cancer Institute, Durham, North Carolina, USA; Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) (K.S.), Durham VA Health Care System, Durham, North Carolina, USA
| | - Devon K Check
- Department of Population Health Sciences (K.I.P., K.S., D.K.C.), Duke University, Durham, North Carolina, USA
| | - Kristen Lakis
- Office of Culture and Wellbeing Hub (K.L.), Duke University Health System, Durham North Carolina, USA
| | - Lorrie Schmid
- Social Sciences Research Institute (L.S.), Duke University, Durham, North Carolina, USA
| | - Jessica E Ma
- Division of General Internal Medicine, Department of Medicine (N.S., J.W., D.C., K.S., J.M.), Duke University School of Medicine, Durham, North Carolina, USA; Geriatric Research Education and Clinical Center (J.M.), Durham VA Health System, Duke University School of Medicine, Durham, North Carolina, USA.
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Niangoran S, Journot V, Marcy O, Anglaret X, Alioum A. Performance of four centralized statistical monitoring methods for early detection of an atypical center in a multicenter study. Contemp Clin Trials Commun 2023; 34:101168. [PMID: 37425338 PMCID: PMC10328794 DOI: 10.1016/j.conctc.2023.101168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/02/2023] [Accepted: 06/18/2023] [Indexed: 07/11/2023] Open
Abstract
Background Ensuring the quality of data is essential for the credibility of a multicenter clinical trial. Centralized Statistical Monitoring (CSM) of data allows the detection of a center in which the distribution of a specific variable is atypical compared to other centers. The ideal CSM method should allow early detection of problem and therefore involve the fewest possible participants. Methods We simulated clinical trials and compared the performance of four CSM methods (Student, Hatayama, Desmet, Distance) to detect whether the distribution of a quantitative variable was atypical in one center in relation to the others, with different numbers of participants and different mean deviation amplitudes. Results The Student and Hatayama methods had good sensitivity but poor specificity, which disqualifies them for practical use in CSM. The Desmet and Distance methods had very high specificity for detecting all the mean deviations tested (including small values) but low sensitivity with mean deviations less than 50%. Conclusion Although the Student and Hatayama methods are more sensitive, their low specificity would lead to too many alerts being triggered, which would result in additional unnecessary control work to ensure data quality. The Desmet and Distance methods have low sensitivity when the deviation from the mean is low, suggesting that the CSM should be used alongside other conventional monitoring procedures rather than replacing them. However, they have excellent specificity, which suggests they can be applied routinely, since using them takes up no time at central level and does not cause any unnecessary workload in investigating centers.
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Affiliation(s)
- Serge Niangoran
- University of Bordeaux, National Institute for Health and Medical Research (INSERM) UMR 1219, Bordeaux Population Health Research Center, Bordeaux, France
- Research Institute for Sustainable Development (IRD) EMR 271, Bordeaux, France
- Programme PACCI, Abidjan, Côte d'Ivoire
| | - Valérie Journot
- University of Bordeaux, National Institute for Health and Medical Research (INSERM) UMR 1219, Bordeaux Population Health Research Center, Bordeaux, France
- Research Institute for Sustainable Development (IRD) EMR 271, Bordeaux, France
| | - Olivier Marcy
- University of Bordeaux, National Institute for Health and Medical Research (INSERM) UMR 1219, Bordeaux Population Health Research Center, Bordeaux, France
- Research Institute for Sustainable Development (IRD) EMR 271, Bordeaux, France
| | - Xavier Anglaret
- University of Bordeaux, National Institute for Health and Medical Research (INSERM) UMR 1219, Bordeaux Population Health Research Center, Bordeaux, France
- Research Institute for Sustainable Development (IRD) EMR 271, Bordeaux, France
| | - Amadou Alioum
- University of Bordeaux, National Institute for Health and Medical Research (INSERM) UMR 1219, Bordeaux Population Health Research Center, Bordeaux, France
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Wang L, Chen L, Jia F, Shi X, Zhang Y, Li F, Hao Y, Hou Y, Deng H, Zhang J, Huang L, Xie X, Fang S, Xu Q, Xu L, Guan H, Wang W, Shen J, Li F, Qian Y, Wang X, Shan L, Tan C, Wang J, Yu Y, Wang X, Zhang L, Li X, Ke X, Li T. Risk factors and prediction nomogram model for psychosocial and behavioural problems among children and adolescents during the COVID-19 pandemic: A national multicentre study: Risk Factors of Childhood Psychosocial Problems. J Affect Disord 2021; 294:128-136. [PMID: 34284318 PMCID: PMC8433597 DOI: 10.1016/j.jad.2021.06.077] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/27/2021] [Accepted: 06/28/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND We aimed to explore the risk profiles attributable to psychosocial and behavioural problems during the coronavirus disease 2019 pandemic. To this end, we created a risk-prediction nomogram model. METHODS A national multicentre study was conducted through an online questionnaire involving 12,186 children (6-11 years old) and adolescents (12-16 years old). Respondents' psychosocial and behavioural functioning were assessed using the Achenbach Child Behaviour Checklist (CBCL). Data were analysed using STATA software and R-language. RESULTS The positive detection rate of psychological problems within Wuhan was greater than that outside Wuhan for schizoid (P = 0.005), and depression (P = 0.030) in children, and for somatic complaints (P = 0.048), immaturity (P = 0.023), and delinquent behaviour (P = 0.046) in adolescents. After graded multivariable adjustment, seven factors associated with psychological problems in children and adolescents outside Wuhan were parent-child conflict (odds ratio (OR): 4.94, 95% confidence interval (95% CI): 4.27-5.72), sleep problems (OR: 4.05, 95% CI: 3.77-4.36), online study time (OR: 0.41, 95% CI: 0.37-0.47), physical activity time (OR: 0.510, 95% CI: 0.44-0.59), number of close friends (OR: 0.51, 95% CI: 0.44-0.6), time spent playing videogames (OR: 2.26, 95% CI: 1.90-2.69) and eating disorders (OR: 2.71, 95% CI: 2.35-3.11) (all P < 0.001). Contrastingly, within Wuhan, only the first four factors, namely, parent-child conflict (5.95, 2.82-12.57), sleep problems (4.47, 3.06-6.54), online study time (0.37, 0.22-0.64), and physical activity time (0.42, 0.22-0.80) were identified (all P < 0.01). Accordingly, nomogram models were created with significant attributes and had decent prediction performance with C-indexes over 80%. LIMITATION A cross-sectional study and self-reported measures. CONCLUSIONS Besides the four significant risk factors within and outside Wuhan, the three additional factors outside Wuhan deserve special attention. The prediction nomogram models constructed in this study have important clinical and public health implications for psychosocial and behavioural assessment.
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Affiliation(s)
- Lin Wang
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Li Chen
- National Clinical Research Center for Child Health and Disorder, Children's Hospital of Chongqing Medical University, Chongqing, China
| | - Feiyong Jia
- Department of Developmental-Behavioral Pediatrics, the First Hospital of Jilin University, Changchun, Jilin, China
| | - Xinmiao Shi
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Yiwen Zhang
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center Affiliated to Medical School of Shanghai Jiaotong University, Shanghai, China
| | - Fei Li
- Department of Developmental-Behavioral Pediatrics, Xinhua Hospital Affiliated to Medical School of Shanghai Jiaotong University, Shanghai, China
| | - Yan Hao
- Department of Child Health Care, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yan Hou
- Department of Biostatistics, Peking University, Beijing, China
| | - Hongzhu Deng
- Child Developmental & Behavioral Center, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jie Zhang
- Department of Child Health Care, Xi'an Children's Hospital, Xi'an, Shaanxi, China
| | - Linjuan Huang
- Health Management Center, Fuzhou Children's Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Xianghui Xie
- Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Shuanfeng Fang
- Department of Child Health Care, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, Henan, China
| | - Qi Xu
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Liang Xu
- WHO Collaborating Center for Research and Training in Child Mental health, Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongyan Guan
- Department of Early Childhood Development, Capital Institute of Pediatrics, Beijing, China
| | - Weijie Wang
- Shanghai Pudong Institute of Education Development, Shanghai, China
| | - Jianna Shen
- Chongqing educational science research academy, Chongqing, China
| | - Feng Li
- Jiangjin centre hospital, chongqing, China
| | - Ying Qian
- Peking University Sixth Hospital, Peking University Institute of Mental Health, National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University), Beijing, China
| | - Xi Wang
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Ling Shan
- Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center Affiliated to Medical School of Shanghai Jiaotong University, Shanghai, China
| | - Chuanxue Tan
- Department of Child Health Care, Xi'an Children's Hospital, Xi'an, Shaanxi, China
| | - Jianhong Wang
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Yabin Yu
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Xiaoyan Wang
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Lili Zhang
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Xiaomeng Li
- Department of Child Health Care, Children's Hospital, Capital Institute of Pediatrics, Beijing, China
| | - Xiaoyan Ke
- WHO Collaborating Center for Research and Training in Child Mental health, Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu, China.
| | - Tingyu Li
- National Clinical Research Center for Child Health and Disorder, Children's Hospital of Chongqing Medical University, Chongqing, China.
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Rifas-Shiman SL, Huh SY, Martin RM, Kramer M, Patel R, Bogdanovich N, Vilchuck K, Thompson J, Oken E. Delivery by caesarean section and offspring adiposity and cardio-metabolic health at ages 6.5, 11.5 and 16 years: results from the PROBIT cohort in Belarus. Pediatr Obes 2021; 16:e12783. [PMID: 33660413 DOI: 10.1111/ijpo.12783] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 02/01/2021] [Accepted: 02/08/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND Caesarean delivery has been associated with later adiposity, perhaps via early programming or perhaps because of residual confounding by maternal or birth characteristics. OBJECTIVES Examine associations of caesarean delivery with adiposity and cardio-metabolic biomarkers. METHODS Observational analysis of 15 069 children in the PROBIT cohort in Belarus. We examined measures of child anthropometry and blood pressure at 6.5, 11.5 and 16 years and fasting blood (11.5 years). RESULTS Caesarean-delivered children were slightly heavier at 6.5 (mean BMI 15.8 vs. 15.6 kg/m2 ), 11.5 (18.4 vs. 18.2) and 16 years (21.5 vs. 21.3). After adjustment for prenatal characteristics including maternal third trimester BMI, however, we observed no association of caesarean versus vaginal delivery with child BMI (β 0.05 kg/m2 ; 95%CI: -0.03, 0.14), sum of skinfolds (0.14 mm; -0.13, 0.42), waist circumference (-0.07 cm; -0.23, 0.10), obesity (OR 0.99; 0.76, 1.29), or systolic (-0.20 mmHg; -0.70, 0.30) or diastolic (-0.17 mmHg, -0.60, 0.26) blood pressure at 6.5 years; results were similar at 11.5 and 16 years. At 11.5 years, we observed a modest association of caesarean delivery with fasting insulin (0.33 mU/L; 0.00, 0.65). CONCLUSIONS Caesarean delivery had little or no association with adiposity or related cardio-metabolic biomarkers in childhood. Adjustment for maternal BMI attenuated all outcome effect estimates.
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Affiliation(s)
- Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Susanna Y Huh
- Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Richard M Martin
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Michael Kramer
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Rita Patel
- Department of Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Natalia Bogdanovich
- Department of Obstetrics, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Konstanin Vilchuck
- Department of Obstetrics, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Jennifer Thompson
- Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
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Association of pre- and early-pregnancy factors with the risk for gestational diabetes mellitus in a large Chinese population. Sci Rep 2021; 11:7335. [PMID: 33795771 PMCID: PMC8016847 DOI: 10.1038/s41598-021-86818-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 03/19/2021] [Indexed: 02/07/2023] Open
Abstract
Gestational diabetes mellitus (GDM) has aroused wide public concern, as it affects approximately 1.8-25.1% of pregnancies worldwide. This study aimed to examine the association of pre-pregnancy demographic parameters and early-pregnancy laboratory biomarkers with later GDM risk, and further to establish a nomogram prediction model. This study is based on the big obstetric data from 10 "AAA" hospitals in Xiamen. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria. Data are analyzed using Stata (v14.1) and R (v3.5.2). Total 187,432 gestational women free of pre-pregnancy diabetes mellitus were eligible for analysis, including 49,611 women with GDM and 137,821 women without GDM. Irrespective of confounding adjustment, eight independent factors were consistently and significantly associated with GDM, including pre-pregnancy body mass index (BMI), pre-pregnancy intake of folic acid, white cell count, platelet count, alanine transaminase, albumin, direct bilirubin, and creatinine (p < 0.001). Notably, per 3 kg/m2 increment in pre-pregnancy BMI was associated with 22% increased risk [adjusted odds ratio (OR) 1.22, 95% confidence interval (CI) 1.21-1.24, p < 0.001], and pre-pregnancy intake of folic acid can reduce GDM risk by 27% (adjusted OR 0.73, 95% CI 0.69-0.79, p < 0.001). The eight significant factors exhibited decent prediction performance as reflected by calibration and discrimination statistics and decision curve analysis. To enhance clinical application, a nomogram model was established by incorporating age and above eight factors, and importantly this model had a prediction accuracy of 87%. Taken together, eight independent pre-/early-pregnancy predictors were identified in significant association with later GDM risk, and importantly a nomogram modeling these predictors has over 85% accuracy in early detecting pregnant women who will progress to GDM later.
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Meske DS, Vaughn BJ, Kopecky EA, Katz N. Number Of Clinical Trial Study Sites Impacts Observed Treatment Effect Size: An Analysis Of Randomized Controlled Trials Of Opioids For Chronic Pain. J Pain Res 2019; 12:3161-3165. [PMID: 31819600 PMCID: PMC6875508 DOI: 10.2147/jpr.s201751] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 10/22/2019] [Indexed: 12/31/2022] Open
Abstract
Background Many aspects of study conduct impact the observed effect size of treatment. Data were utilized from a recently published meta-analysis of randomized, double-blind, placebo-controlled, clinical trials performed for the United States Food and Drug Administration (FDA) approval of full mu-agonist opioids for the treatment of chronic pain. Methods The number of study sites in each clinical trial and standardized effect size (SES) were extracted and computed. Standardized effect size was plotted against number of sites, and a two-piece linear model was fit to the plot. Ten studies were included. Results The SES decreased linearly by 0.13 units for every 10 sites (p=0.037), from 0.75 to 0.36, until an inflection point of 60 sites, after which SES did not decline further. The total number of subjects required for 90% power to discriminate drug from placebo increased from 78 to 336 subjects going from 30 to 60 sites. Conclusion Results showed that the number of sites was a source of loss of assay sensitivity in clinical trials, which may contribute to the well-known problem of failure to successfully transition from Phase 2 to Phase 3 clinical development. Potential solutions include minimizing the number of sites, more rigorous and validated training, central statistical monitoring with rapid correction of performance issues, and more rigorous subject and site selection.
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Affiliation(s)
| | | | | | - Nathaniel Katz
- WCG Analgesic Solutions, Wayland, MA, USA.,Department of Anesthesia, Tufts University School of Medicine, Boston, MA, USA
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Aris IM, Rifas-Shiman SL, Zhang X, Yang S, Switkowski K, Fleisch AF, Hivert MF, Martin RM, Kramer MS, Oken E. Association of BMI with Linear Growth and Pubertal Development. Obesity (Silver Spring) 2019; 27:1661-1670. [PMID: 31479205 PMCID: PMC6756952 DOI: 10.1002/oby.22592] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Accepted: 06/18/2019] [Indexed: 12/29/2022]
Abstract
OBJECTIVE The aim of this study was to investigate the relationship of BMI with subsequent statural growth among children born in the era of the obesity epidemic. METHODS Among 18,271 children from Belarus (n = 16,781, born 1996 to 1997) and the United States (n = 1,490, born 1999 to 2002), multivariable linear and ordinal logistic regression was used to analyze associations of BMI z score from infancy to adolescence with subsequent standardized length and height velocity, standing height and its components (trunk and leg lengths), and pubertal timing. RESULTS The prevalence of early adolescent obesity was 6.2% in Belarus and 12.8% in the United States. In both Belarusian and US children, higher BMI z scores in infancy and childhood were associated with faster length and height velocity in early life, while higher BMI z scores during middle childhood were associated with slower length and height velocity during adolescence. Associations with greater standing height and trunk length and earlier pubertal development in adolescence were stronger for BMI z scores at middle childhood than BMI z scores at birth or infancy. CONCLUSIONS These findings in both Belarus and the United States support the role of higher BMI in accelerating linear growth in early life (taller stature and longer trunk length) but earlier pubertal development and slower linear growth during adolescence.
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Affiliation(s)
- Izzuddin M Aris
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - Sheryl L Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Xun Zhang
- Centre for Outcomes Research and Evaluation, McGill University Health Centre Research Institute, Montreal, Quebec, Canada
| | - Seungmi Yang
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Karen Switkowski
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
| | - Abby F Fleisch
- Pediatric Endocrinology and Diabetes, Maine Medical Center, Portland, Maine, USA
- Center for Outcomes Research and Evaluation, Maine Medical Center Research Institute, Portland, Maine, USA
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Richard M Martin
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals NHS Trust and University of Bristol, Bristol, UK
| | - Michael S Kramer
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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Södersten P, Brodin U, Sjöberg J, Zandian M, Bergh C. Treatment outcomes for eating disorders in Sweden: data from the national quality registry. BMJ Open 2019; 9:e024179. [PMID: 30647041 PMCID: PMC6340438 DOI: 10.1136/bmjopen-2018-024179] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
OBJECTIVE To report the outcomes of eating disorders treatment in Sweden in 2012-2016. DESIGN The number of patients treated and the number of patients not fulfilling an eating disorders diagnosis (remission) at 1 year of follow-up at the clinics listed in the National Quality Registry for Eating Disorders Treatment were analysed. The published outcomes at three clinics, which used survival analysis to estimate outcomes, were compared with their outcomes in the registry. Outcomes at the three biggest clinics were compared. SETTING All eating disorders clinics. PARTICIPANTS All patients treated at eating disorders clinics. INTERVENTION Cognitive-behavioural therapy at most clinics and normalisation of eating behaviour at the three clinics with published outcomes. OUTCOME MEASURE Proportion of patients in remission. RESULTS About 2600 patients were treated annually, fewer than half were followed up and remission rates decreased from 21% in 2014 to 14% in 2016. Outcomes, which differed among clinics and within clinics over time, have been publicly overestimated by excluding patients lost to follow-up. The published estimated rate of remission at three clinics that treated 1200 patients in 1993-2011 was 27%, 28% and 40% at 1 year of follow-up. The average rate of remission over the three last years at the biggest of these clinics was 36% but decreased from 29% and 30% to 16 and 14% at the two other of the biggest clinics. CONCLUSIONS With more than half the patients lost to follow-up and no data on relapse in the National Quality Registry, it is difficult to estimate the effects of eating disorders treatment in Sweden. Analysis of time to clinically significant events, including an extended period of follow-up, has improved the quality of the estimates at three clinics. Overestimation of remission rates has misled healthcare policies. The effect of eating disorders treatment has also been overestimated internationally.
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Affiliation(s)
- Per Södersten
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Mandometer Clinic, Huddinge, Sweden
| | - Ulf Brodin
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Mandometer Clinic, Huddinge, Sweden
| | | | - Modjtaba Zandian
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Mandometer Clinic, Huddinge, Sweden
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Aris IM, Rifas-Shiman SL, Li LJ, Yang S, Belfort MB, Thompson J, Hivert MF, Patel R, Martin RM, Kramer MS, Oken E. Association of Weight for Length vs Body Mass Index During the First 2 Years of Life With Cardiometabolic Risk in Early Adolescence. JAMA Netw Open 2018; 1:e182460. [PMID: 30646168 PMCID: PMC6324504 DOI: 10.1001/jamanetworkopen.2018.2460] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Accepted: 07/11/2018] [Indexed: 12/17/2022] Open
Abstract
Importance The American Academy of Pediatrics currently recommends weight for length (WFL) for assessment of weight status in children younger than 2 years but body mass index (BMI) for children older than 2 years. However, the clinical implications of using WFL vs BMI in children younger than 2 years as an indicator of future health outcomes remains understudied. Objective To compare associations of overweight based on WFL vs BMI in children younger than 2 years with cardiometabolic outcomes during early adolescence. Design, Setting, and Participants This prospective study of birth cohorts in the United States (Project Viva) and Belarus (Promotion of Breastfeeding Intervention Trial [PROBIT]) performed from June 1, 1996, to November 31, 2002, included 13 666 children younger than 2 years. Main Exposures Overweight defined as Centers for Disease Control and Prevention (CDC) WFL in the 95th percentile or greater, World Health Organization (WHO) WFL in the 97.7th percentile or greater, or WHO BMI in the 97.7th percentile or greater at 6, 12, 18, or 24 months of age. Main Outcomes and Measures Primary outcomes were fat mass index, insulin resistance, metabolic risk score, and obesity during early adolescence. Secondary outcomes were height and BMI z scores, sum of skinfolds, waist circumference, and systolic blood pressure during early adolescence. Results The study included 919 children (mean [SD] age, 12.9 [0.9] years; 460 [50.1%] male; and 598 [65.1%] white) from Project Viva and 12 747 children (mean [SD] age, 11.5 [0.5] years; 6204 [48.7%] male; and 12 747 [100%] white) from PROBIT. During 6 to 24 months of age, in Project Viva, 206 children (22.4%) were overweight at any of the 4 times points according to the CDC WFL, 160 (17.4%) according to WHO WFL, and 161 (17.5%) according to WHO BMI cut points. In PROBIT, 3715 children (29.1%) were overweight at any of the 4 time points according to the CDC WFL, 3069 (24.1%) according to WHO WFL, and 3125 (24.5%) according to WHO BMI cut points. After maternal and child characteristics were adjusted for, being ever overweight (vs never overweight) during 6 to 24 months of age was associated with higher likelihood of adverse cardiometabolic risk markers during early adolescence, but associations did not differ substantially across WFL and BMI cut points in either cohort. For example, for fat mass index in Project Viva, β = 0.9 (95% CI, 0.5-1.4) for the CDC WFL, β = 1.1 (95% CI, 0.6-1.6) for WHO WFL, and β = 1.4 (95% CI, 0.9-1.9) for WHO BMI. For PROBIT, β = 0.5 (95% CI, 0.4-0.6) for the CDC WFL, β = 0.6 (95% CI, 0.5-0.7) for WHO WFL, and β = 0.6 (95% CI, 0.5-0.6) for WHO BMI. Neither growth metric in infancy was superior over the others based on F statistics (Project Viva: 17.1-17.8; PROBIT: 87.1-88.7). Findings were similar for insulin resistance, metabolic risk score, obesity, and secondary outcomes. Conclusions and Relevance Choice of WFL vs BMI to define overweight during the first 2 years of life may not greatly affect the association with cardiometabolic outcomes during early adolescence. The findings appear to have important implications for investigators seeking to use BMI as a growth metric for epidemiologic research and for practitioners monitoring the weight status of children younger than 2 years.
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Affiliation(s)
- Izzuddin M. Aris
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Sheryl L. Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Ling-Jun Li
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Division of Obstetrics and Gynecology, KK Women’s and Children’s Hospital, Singapore, Singapore
- Obstetrics and Gynecology Academic Clinical Programme, Duke–National University of Singapore Graduate Medical School, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Seungmi Yang
- Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine McGill University, Montreal, Quebec, Canada
| | - Mandy B. Belfort
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Jennifer Thompson
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Diabetes Unit, Massachusetts General Hospital, Boston
| | - Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Richard M. Martin
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Michael S. Kramer
- Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine McGill University, Montreal, Quebec, Canada
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
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10
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Owen CG, Oken E, Rudnicka AR, Patel R, Thompson J, Rifas-Shiman SL, Vilchuck K, Bogdanovich N, Hameza M, Kramer MS, Martin RM. The Effect of Longer-Term and Exclusive Breastfeeding Promotion on Visual Outcome in Adolescence. Invest Ophthalmol Vis Sci 2018; 59:2670-2678. [PMID: 29860453 PMCID: PMC5983062 DOI: 10.1167/iovs.17-23211] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Purpose Breastfeeding may influence early visual development. We examined whether an intervention to promote increased duration and exclusivity of breastfeeding improves visual outcomes at 16 years of age. Methods Follow-up of a cluster-randomized trial in 31 Belarusian maternity hospitals/polyclinics randomized to receive a breastfeeding promotion intervention, or usual care, where 46% vs. 3% were exclusively breastfed at 3 months respectively. Low vision in either eye was defined as unaided logMAR vision of ≥0.3 or worse (equivalent to Snellen 20/40) and was used as the primary outcome. Open-field autorefraction in a subset (n = 963) suggested that 84% of those with low vision were myopic. Primary analysis was based on modified intention-to-treat, accounting for clustering within hospitals/clinics. Observational analyses also examined the effect of breastfeeding duration and exclusivity, as well as other sociodemographic and environmental determinants of low vision. Results A total of 13,392 of 17,046 (79%) participants were followed up at 16 years. Low vision prevalence was 19.6% (95% confidence interval [CI]: 17.5, 22.0%) in the experimental group versus 21.6% (19.5, 23.8%) in the control group. Cluster-adjusted odds ratio (OR) of low vision associated with the intervention was 0.92 (95% CI: 0.73, 1.16); 0.88 (95% CI: 0.74, 1.05) after adjustment for parental and early life factors. In observational analyses, breastfeeding duration and exclusivity had no significant effect on low vision. However, maternal age at birth (OR: 1.13, 95% CI: 1.07, 1.14/5-year increase) and urban versus rural residence were associated with increased risk of low vision. Lower parental education, number of older siblings was associated with a lower risk of low vision; boys had lower risk compared with girls (0.64, 95% CI: 0.59,0.70). Conclusions Exclusive breastfeeding promotion had no significant effect on visual outcomes in this study, but other environmental factors showed strong associations. (ClinicalTrials.gov number, NCT01561612.)
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Affiliation(s)
- Christopher G Owen
- Population Health Research Institute, St. George's, University of London, Cranmer Terrace, London, United Kingdom
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States
| | - Alicja R Rudnicka
- Population Health Research Institute, St. George's, University of London, Cranmer Terrace, London, United Kingdom
| | - Rita Patel
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Jennifer Thompson
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States
| | - Konstatin Vilchuck
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Natalia Bogdanovich
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Mikhail Hameza
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Michael S Kramer
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada
| | - Richard M Martin
- Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, United Kingdom.,University Hospitals Bristol NHS Foundation Trust and University of Bristol National Institute for Health Research Bristol Biomedical Research Centre, Bristol, United Kingdom.,Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
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11
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Yang S, Martin RM, Oken E, Hameza M, Doniger G, Amit S, Patel R, Thompson J, Rifas-Shiman SL, Vilchuck K, Bogdanovich N, Kramer MS. Breastfeeding during infancy and neurocognitive function in adolescence: 16-year follow-up of the PROBIT cluster-randomized trial. PLoS Med 2018; 15:e1002554. [PMID: 29677187 PMCID: PMC5909901 DOI: 10.1371/journal.pmed.1002554] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2017] [Accepted: 03/15/2018] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Evidence on the long-term effect of breastfeeding on neurocognitive development is based almost exclusively on observational studies. In the 16-year follow-up study of a large, cluster-randomized trial of a breastfeeding promotion intervention, we evaluated the long-term persistence of the neurocognitive benefits of the breastfeeding promotion intervention previously observed at early school age. METHODS AND FINDINGS A total of 13,557 participants (79.5% of the 17,046 randomized) of the Promotion of Breastfeeding Intervention Trial (PROBIT) were followed up at age 16 from September 2012 to July 2015. At the follow-up, neurocognitive function was assessed in 7 verbal and nonverbal cognitive domains using a computerized, self-administered test battery among 13,427 participants. Using an intention-to-treat (ITT) analysis as our prespecified primary analysis, we estimated cluster- and baseline characteristic-adjusted mean differences between the intervention (prolonged and exclusive breastfeeding promotion modelled on the Baby-Friendly Hospital Initiative) and control (usual care) groups in 7 cognitive domains and a global cognitive score. In our prespecified secondary analysis, we estimated mean differences by instrumental variable (IV) analysis to account for noncompliance with the randomly assigned intervention and estimate causal effects of breastfeeding. The 16-year follow-up rates were similar in the intervention (79.7%) and control groups (79.3%), and baseline characteristics were comparable between the two. In the cluster-adjusted ITT analyses, children in the intervention group did not show statistically significant differences in the scores from children in the control group. Prespecified additional adjustment for baseline characteristics improved statistical precision and resulted in slightly higher scores among children in the intervention for verbal function (1.4 [95% CI 0.3-2.5]) and memory (1.2 [95% CI 0.01-2.4]). IV analysis showed that children who were exclusively breastfed for ≥3 (versus <3) months had a 3.5-point (95% CI 0.9-6.1) higher verbal function, but no differences were observed in other domains. While our computerized, self-administered cognitive testing reduced the cluster-level variability in the scores, it may have increased individual-level measurement errors in adolescents. CONCLUSIONS We observed no benefit of a breastfeeding promotion intervention on overall neurocognitive function. The only beneficial effect was on verbal function at age 16. The higher verbal ability is consistent with results observed at early school age; however, the effect size was substantially smaller in adolescence. PROBIT TRIAL REGISTRATION ClinicalTrials.gov NCT01561612.
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Affiliation(s)
- Seungmi Yang
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Richard M. Martin
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
- University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, United Kingdom
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America
| | - Mikhail Hameza
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Glen Doniger
- NeuroTrax Corporation, Medina, New York, United States of America
| | - Shimon Amit
- NeuroTrax Corporation, Medina, New York, United States of America
| | - Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Jennifer Thompson
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America
| | - Sheryl L. Rifas-Shiman
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts, United States of America
| | - Konstantin Vilchuck
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Natalia Bogdanovich
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Michael S. Kramer
- Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
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12
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Flohr C, Henderson AJ, Kramer MS, Patel R, Thompson J, Rifas-Shiman SL, Yang S, Vilchuck K, Bogdanovich N, Hameza M, Martin RM, Oken E. Effect of an Intervention to Promote Breastfeeding on Asthma, Lung Function, and Atopic Eczema at Age 16 Years: Follow-up of the PROBIT Randomized Trial. JAMA Pediatr 2018; 172:e174064. [PMID: 29131887 PMCID: PMC6583261 DOI: 10.1001/jamapediatrics.2017.4064] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
IMPORTANCE Atopic diseases, including asthma and atopic eczema, are the most common chronic conditions of childhood. OBJECTIVE To investigate whether an intervention to promote prolonged and exclusive breastfeeding protects against asthma, atopic eczema, and low lung function in adolescence. DESIGN, SETTING, AND PARTICIPANTS Follow-up of the Promotion of Breastfeeding Intervention Trial (PROBIT), a cluster randomized trial in 30 Belarusian maternity hospitals and affiliated polyclinics; recruitment of 17 046 healthy term infants took place from June 15, 1996, to December 31, 1997. Data analysis was conducted from May 9, 2016, to April 21, 2017. The primary analytic approach was by modified intention-to-treat analysis. INTERVENTIONS Randomization to receive a breastfeeding promotion intervention vs usual care. MAIN OUTCOMES AND MEASURES Spirometry and flexural eczema on standardized skin examination by study pediatricians were the primary outcomes; secondary outcomes were self-reported asthma diagnosis ever, and wheezing and flexural eczema symptoms in the previous year. RESULTS A total of 13 557 (79.5%) participants were followed up from September 15, 2012 to July 15, 2015. The intervention (7064 [79.7%]) and control (6493 [79.4%]) groups were similar at follow-up (3590 [50.8%] and 3391 [52.2%] male; mean [SD] age, 16.2 [0.6] and 16.1 [0.5] years, respectively). In the intervention group, 0.3% (21 of 7064) had flexural eczema on skin examination and mean (SD) forced expiratory volume in the first second of expiration/forced vital capacity (FEV1/FVC) ratio z score was -0.10 (1.82), compared with 0.7% (43 of 6493) and 0.35 (1.34), respectively, in the control group. In modified intention-to-treat analysis, accounting for clustering by polyclinic, a 54% lower risk of flexural eczema on skin examination was observed in the intervention compared with the control group (odds ratio [OR], 0.46; 95% CI, 0.25 to 0.86). Self-reported flexural eczema symptoms in the past year (OR, 0.57; 95% CI, 0.27 to 1.18), asthma (OR, 0.76; 95% CI, 0.47 to 1.23), and wheezing in the past year (OR, 0.66; 95% CI, 0.37 to 1.18) were less frequently reported in the intervention compared with the control group, but 95% CIs were wide and included the null. There was no significant difference in the FEV1/FVC ratio z score (β -0.15; 95% CI, -0.76 to 0.45). All results were similar with additional adjustment for baseline characteristics, on instrumental variable analysis, and with multiple imputation among all 17 046 randomized participants. CONCLUSIONS AND RELEVANCE A breastfeeding promotion intervention reduced flexural dermatitis risk but had no detectable effect on lung function or questionnaire-derived measures of atopic eczema or asthma in adolescence in a setting where atopic eczema and allergies are rare. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01561612.
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Affiliation(s)
- Carsten Flohr
- Unit for Population-Based Dermatology Research, St John’s Institute of Dermatology, Division of Genetics and Molecular Medicine, King’s College London and Guy’s & St Thomas’ National Health Service Foundation Trust, London, England
| | - A. John Henderson
- School of Social and Community Medicine, University of Bristol, Bristol, England
| | - Michael S. Kramer
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, England
| | - Jennifer Thompson
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Sheryl L. Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
| | - Seungmi Yang
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada,Department of Pediatrics, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Konstantin Vilchuck
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Natalia Bogdanovich
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Mikhail Hameza
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Richard M. Martin
- School of Social and Community Medicine, University of Bristol, Bristol, England,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, England
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, Massachusetts
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Khan NA, Spencer HJ, Nikiphorou E, Naranjo A, Alten R, Chirieac RM, Drosos AA, Géher P, Inanc N, Kerzberg E, Ancuta CM, Müller R, Ørnbjerg L, Sokka T. Intercentre variance in patient reported outcomes is lower than objective rheumatoid arthritis activity measures: a cross-sectional study. Rheumatology (Oxford) 2017; 56:1395-1400. [PMID: 28575509 DOI: 10.1093/rheumatology/kex076] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Indexed: 01/18/2023] Open
Abstract
Objective To assess intercentre variability in the ACR core set measures, DAS28 based on three variables (DAS28v3) and Routine Assessment of Patient Index Data 3 in a multinational study. Methods Seven thousand and twenty-three patients were recruited (84 centres; 30 countries) using a standard protocol in the Quantitative Standard Monitoring of Patients with RA study. Analysis of variance (ANOVA) and mixed-effect analysis of covariance models were used to model the relationship between study centre and different patient-reported and physician-reported RA activity measures. These models were built to adjust for the remaining ACR core set measure (for each ACR core set measure or each composite index), socio-demographics and medical characteristics. ANOVA and analysis of covariance models yielded similar results, and ANOVA tables were used to present variance attributable to recruiting centre. Results The proportion of variances attributable to recruiting centre was lower for patient reported outcomes (PROs: pain, HAQ, patient global) compared with objective measures (joint counts, ESR, physician global) in all models. In the full model, variance in PROs attributable to recruiting centre ranged from 1.53% for patient global to 3.71% for HAQ compared with objective measures that ranged from 5.92% for physician global to 9.25% for ESR; and was lower for Routine Assessment of Patient Index Data 3 (2.6%) compared with DAS28v3 (11.75%). Conclusion Intercentre variability in PROs is lower than objective measures of RA activity demonstrating that PROs may be more comparable across centres, and the need for standardization of objective measures.
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Affiliation(s)
- Nasim Ahmed Khan
- Division of Rheumatology, University of Arkansas for Medical Sciences.,Central Arkansas Veterans Healthcare System
| | - Horace Jack Spencer
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Elena Nikiphorou
- Department of Rheumatology, The Whittington Hospital NHS Trust, London, UK
| | - Antonio Naranjo
- Department of Rheumatology, Hospital Universitario de Gran Canaria Dr Negrin, University of Las Palmas, Las Palmas, Spain
| | - Rieki Alten
- Department of Internal Medicine, Rheumatology, Schlosspark-Klinik, Teaching Hospital Charite, Berlin, Germany
| | | | - Alexandros A Drosos
- Department of Internal Medicine, Medical School, University of Ioannina, Ioannina, Greece
| | - Pál Géher
- 1st Department of Rheumatology, Hospitaller Brothers of St John of God, Budapest, Hungary
| | - Nevsun Inanc
- Division of Rheumatology, School of Medicine, University of Marmara, Istanbul, Turkey
| | - Eduardo Kerzberg
- Department of Rheumatology, University of Buenos Aires, Buenos Aires, Argentina
| | - Codrina Mihaela Ancuta
- Rheumatology 2 Department, "Grigore T. Popa" University of Medicine and Pharmacy, Iasi, Romania
| | - Rüediger Müller
- Division of Rheumatology, Immunology and Rehabilitation, Kantonsspital St Gallen, St Gallen, Switzerland
| | - Lykke Ørnbjerg
- Copenhagen Center for Arthritis Research, Center for Rheumatology and Spine Diseases, Rigshospitalet Glostrup, Denmark
| | - Tuulliki Sokka
- University of Eastern Finland, Faculty of Health Sciences, Kuopio and Jyvaskyla Central Hospital, Jyvaskyla, Finland
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Martin RM, Kramer MS, Patel R, Rifas-Shiman SL, Thompson J, Yang S, Vilchuck K, Bogdanovich N, Hameza M, Tilling K, Oken E. Effects of Promoting Long-term, Exclusive Breastfeeding on Adolescent Adiposity, Blood Pressure, and Growth Trajectories: A Secondary Analysis of a Randomized Clinical Trial. JAMA Pediatr 2017; 171:e170698. [PMID: 28459932 PMCID: PMC5576545 DOI: 10.1001/jamapediatrics.2017.0698] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
IMPORTANCE Evidence that breastfeeding reduces child obesity risk and lowers blood pressure (BP) is based on potentially confounded observational studies. OBJECTIVE To investigate the effects of a breastfeeding promotion intervention on adiposity and BP at age 16 years and on longitudinal growth trajectories from birth. DESIGN, SETTING, AND PARTICIPANTS Cluster-randomized Promotion of Breastfeeding Intervention Trial. Belarusian maternity hospitals and affiliated polyclinics (the clusters) were allocated into intervention (n = 16) or control arms (n = 15) in 1996 and 1997. The trial participants were 17 046 breastfeeding mother-infant pairs; of these, 13 557 children (79.5%) were followed up at 16 years of age between September 2012 and July 2015. INTERVENTIONS Breastfeeding promotion, modeled on the Baby-Friendly Hospital Initiative. MAIN OUTCOMES AND MEASURES Body mass index (BMI, calculated as weight in kilograms divided by height in meters squared); fat and fat-free mass indices and percentage of body fat from bioimpedance; waist circumference; overweight and obesity; height; BP; and longitudinal growth trajectories. The primary analysis was modified intention-to-treat (without imputation for losses to follow-up) accounting for within-clinic clustering. RESULTS We examined 13 557 children at a median age of 16.2 years (48.5% were girls). The intervention substantially increased breastfeeding duration and exclusivity compared with the control arm (exclusively breastfed: 45% vs 6% at 3 months, respectively). Mean differences at 16 years between intervention and control groups were 0.21 (95% CI, 0.06-0.36) for BMI; 0.21 kg/m2 (95% CI, -0.03 to 0.44) for fat mass index; 0.00 kg/m2 (95% CI, -0.21 to 0.22) for fat-free mass index; 0.71% (95% CI, -0.32 to 1.74) for percentage body fat; -0.73 cm (-2.48 to 1.02) for waist circumference; 0.05 cm (95% CI, -0.85 to 0.94) for height; -0.54 mm Hg (95% CI, -2.40 to 1.31) for systolic BP; and 0.71 mm Hg (95% CI, -0.68 to 2.10) for diastolic BP. The odds ratio for overweight/obesity (BMI ≥85th percentile vs <85th percentile) was 1.14 (95% CI, 1.02-1.28) and the odds ratio for obesity (BMI ≥95th percentile vs <95th percentile) was 1.09 (95% CI, 0.92-1.29). The intervention resulted in a more rapid rate of gain in postinfancy height (1 to 2.8 years), weight (2.8 to 14.5 years), and BMI (2.8 to 8.5 years) compared with the control arm. The intervention had little effect on BMI z score changes after 8.5 years. CONCLUSIONS AND RELEVANCE A randomized intervention that increased the duration and exclusivity of breastfeeding was not associated with lowered adolescent obesity risk or BP. On the contrary, the prevalence of overweight/obesity was higher in the intervention arm. All mothers initiated breastfeeding, so findings may not apply to comparisons of the effects of breastfeeding vs formula feeding. TRIAL REGISTRATION isrctn.org: ISRCTN37687716; and clinicaltrials.gov: NCT01561612.
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Affiliation(s)
- Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK, BS8 2PS,University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK,Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK, BS8 2BN
| | - Michael S. Kramer
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada, QC H3A 1A2
| | - Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, UK, BS8 2PS
| | - Sheryl L. Rifas-Shiman
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive Suite 401E, Boston, USA, MA 02215
| | - Jennifer Thompson
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive Suite 401E, Boston, USA, MA 02215
| | - Seungmi Yang
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada, QC H3A 1A2
| | - Konstantin Vilchuck
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Natalia Bogdanovich
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Mikhail Hameza
- National Research and Applied Medicine Mother and Child Centre, Minsk, Republic of Belarus
| | - Kate Tilling
- School of Social and Community Medicine, University of Bristol, Bristol, UK, BS8 2PS
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, 401 Park Drive Suite 401E, Boston, USA, MA 02215
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Borgoni R, Del Bianco P, Salvati N, Schmid T, Tzavidis N. Modelling the distribution of health-related quality of life of advanced melanoma patients in a longitudinal multi-centre clinical trial using M-quantile random effects regression. Stat Methods Med Res 2016; 27:549-563. [DOI: 10.1177/0962280216636651] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Health-related quality of life assessment is important in the clinical evaluation of patients with metastatic disease that may offer useful information in understanding the clinical effectiveness of a treatment. To assess if a set of explicative variables impacts on the health-related quality of life, regression models are routinely adopted. However, the interest of researchers may be focussed on modelling other parts (e.g. quantiles) of this conditional distribution. In this paper, we present an approach based on quantile and M-quantile regression to achieve this goal. We applied the methodologies to a prospective, randomized, multi-centre clinical trial. In order to take into account the hierarchical nature of the data we extended the M-quantile regression model to a three-level random effects specification and estimated it by maximum likelihood.
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Affiliation(s)
- Riccardo Borgoni
- Dipartimento di Economia, Metodi Quantitativi e Strategie d’Impresa, Università di Milano – Bicocca, Milan, Italy
| | - Paola Del Bianco
- Clinical Trials and Biostatistics Unit, Istituto Oncologico Veneto IOV-IRCCS, Padova, Italy
| | - Nicola Salvati
- Dipartimento di Economia e Management, Università di Pisa, Pisa, Italy
| | - Timo Schmid
- Institute of Statistics and Econometrics, Freie Universität Berlin, Berlin, Germany
| | - Nikos Tzavidis
- Department of Social Statistics and Demography, Southampton Statistical Sciences Research Institute, University of Southampton, Southampton, UK
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Gunduz K, Avsever H, Orhan K, Canıtezer G, Acikgoz A, Oz U, Midilli M. A multi-centre evaluation of multiple supernumerary premolar prevalence. AUSTRALASIAN ORTHODONTIC JOURNAL 2015. [DOI: 10.21307/aoj-2020-149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
Abstract
Aim
The occurrence of multiple supernumerary teeth is rare and often found in association with syndromes such as cleidocranial dysplasia, Gardner's syndrome or cleft lip and palate. Few examples of non-syndromal multiple supernumerary teeth have been reported. The aim of this multi-centre study was to investigate the prevalence of supernumerary premolar teeth in non-syndromic patients and to investigate the association between the presence of supernumerary premolar teeth and malocclusion type in a Turkish population.
Materials and methods
The clinical records and panoramic radiographs of 10,700 patients (referred to three different university hospitals) were retrospectively examined for the presence of supernumerary premolars. Age, gender, orthodontic malocclusion type, the number of supernumerary premolars (two or more), the distribution, location, position (vertical, horizontal, inverted, mesio-angular), surgical approach, and related complications (pain, cystic changes, root resorption, or eruption disturbance of adjacent teeth) were recorded.
Results
Forty-two cases (13 Class I, 17 Class II, 12 Class III) of multiple mandibular supernumerary premolars in patients without an associated syndrome were detected. A total of 97 (27 Class I, 41 Class II, 29 Class III) supernumerary premolar teeth were found, with a prevalence of 0.39%. No statistical difference was found related to gender, malocclusion type and supernumerary premolars (p > 0.05). The majority of the extra premolars were located in the mandible, which was statistically significant (p < 0.05).
Conclusion
The present study revealed that the prevalence of multiple supernumerary teeth was 0.39%. The most frequently impacted premolars were found in the mandible and more often associated with Class II malocclusions in the examined Turkish population.
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Affiliation(s)
- Kaan Gunduz
- * Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Ondokuz Mayis University , Samsun , Turkey
| | - Hakan Avsever
- † Department of Dentomaxillofacial Radiology , Dentistry Center , GATA , Ankara , Turkey
| | - Kaan Orhan
- + Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Near East University , Northern Cyprus , Turkey
- ± Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Ankara University , Ankara , Turkey
| | - Gözde Canıtezer
- * Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Ondokuz Mayis University , Samsun , Turkey
| | - Aydan Acikgoz
- * Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Ondokuz Mayis University , Samsun , Turkey
| | - Ulas Oz
- + Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Near East University , Northern Cyprus , Turkey
| | - Muhammet Midilli
- * Faculty of Dentistry , Department of Dentomaxillofacial Radiology , Ondokuz Mayis University , Samsun , Turkey
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Skugarevsky O, Wade KH, Richmond RC, Martin RM, Tilling K, Patel R, Vilchuck K, Bogdanovich N, Sergeichick N, Davey Smith G, Gillman MW, Oken E, Kramer MS. Effects of promoting longer-term and exclusive breastfeeding on childhood eating attitudes: a cluster-randomized trial. Int J Epidemiol 2014; 43:1263-71. [PMID: 24706729 DOI: 10.1093/ije/dyu072] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Observational studies suggest that breastfeeding benefits later maternal child-feeding practices, which in turn may contribute to positive eating attitudes. We investigated the effect of a randomized intervention to increase duration and exclusivity of breastfeeding on pre-adolescent eating attitudes. METHODS Long-term follow-up of the Promotion of Breastfeeding Intervention Trial (PROBIT), a cluster-randomized trial in 31 maternity hospitals and affiliated polyclinics in Belarus. Sites were randomly assigned an experimental intervention to promote longer duration and exclusivity of breastfeeding in mothers who initiated breastfeeding (n = 16 sites), or a control intervention of continuing usual care (n = 15 sites); 17 046 healthy infants were enrolled in 1996-7, of whom 13 751 (80.7%) completed the Children's Eating Attitude Test (ChEAT) at 11.5 years of age. A ChEAT score ≥ 22.5 (85th percentile) was used as an indicator of problematic eating attitudes. Analysis was based on intention-to-treat, accounting for clustering within hospitals/clinics. RESULTS Compared with the control arm, the experimental intervention substantially increased breastfeeding exclusivity (43.3% vs 6.4% exclusively breastfed at 3 months of age) and duration of any breastfeeding throughout infancy. The proportion of children with ChEAT scores ≥ 22.5 was lower in the experimental than control arm (boys 11.4% vs 17.2%; girls 18.5% vs 23.4%) [cluster-adjusted odds ratio (OR), boys: 0.44; 95% confidence interval (CI): 0.21,0.93; girls: 0.51; 95% CI: 0.27,0.99). Results were robust to adjustment for potential confounders and using a ChEAT score ≥ 25.5 (91st percentile) as the outcome (OR: 0.53; 95% CI: 0.28,1.03). CONCLUSIONS An intervention to improve the duration and exclusivity of breastfeeding among term infants in Belarus was associated with a reduction in problematic eating attitudes at 11.5 years of age.
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Affiliation(s)
- Oleg Skugarevsky
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Kaitlin H Wade
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, CanadaPsychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Rebecca C Richmond
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, CanadaPsychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Richard M Martin
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, CanadaPsychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, CanadaPsychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospital
| | - Kate Tilling
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Rita Patel
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Konstantin Vilchuck
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Natalia Bogdanovich
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Natalia Sergeichick
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - George Davey Smith
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, CanadaPsychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Matthew W Gillman
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Emily Oken
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
| | - Michael S Kramer
- Psychiatry and Medical Psychology Department, Belarusian State Medical University, Minsk, Belarus, School of Social and Community Medicine, University of Bristol, Bristol, UK, Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK, University of Bristol / University Hospitals Bristol NHS Foundation Trust National Institute for Health Research Bristol Nutrition Biomedical Research Unit, University of Bristol, Bristol, UK, National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA and Department of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Quebec, Canada
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Martin RM, Patel R, Kramer MS, Vilchuck K, Bogdanovich N, Sergeichick N, Gusina N, Foo Y, Palmer T, Thompson J, Gillman MW, Smith GD, Oken E. Effects of promoting longer-term and exclusive breastfeeding on cardiometabolic risk factors at age 11.5 years: a cluster-randomized, controlled trial. Circulation 2014; 129:321-9. [PMID: 24300437 PMCID: PMC3946966 DOI: 10.1161/circulationaha.113.005160] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2013] [Accepted: 10/15/2013] [Indexed: 11/16/2022]
Abstract
BACKGROUND The duration and exclusivity of breastfeeding in infancy have been inversely associated with future cardiometabolic risk. We investigated the effects of an experimental intervention to promote increased duration of exclusive breastfeeding on cardiometabolic risk factors in childhood. METHODS AND RESULTS We followed-up children in the Promotion of Breastfeeding Intervention Trial, a cluster-randomized trial of a breastfeeding promotion intervention based on the World Health Organization/United Nations Children's Fund Baby-Friendly Hospital Initiative. In 1996 to 1997, 17 046 breastfeeding mother-infant pairs were enrolled from 31 Belarusian maternity hospitals and affiliated polyclinics (16 intervention versus 15 control sites); 13 879 (81.4%) children were followed up at 11.5 years, with 13 616 (79.9%) who had fasted and did not have diabetes mellitus. The outcomes were blood pressure; fasting insulin, adiponectin, glucose, and apolipoprotein A1; and the presence of metabolic syndrome. Analysis was by intention to treat, accounting for clustering within hospitals/clinics. The intervention substantially increased breastfeeding duration and exclusivity in comparison with the control arm (43% versus 6% and 7.9% versus 0.6% exclusively breastfed at 3 and 6 months, respectively). Cluster-adjusted mean differences at 11.5 years between experimental versus control groups were as follows: 1.0 mm Hg (95% confidence interval, -1.1 to 3.1) for systolic and 0.8 mm Hg (-0.6 to 2.3) for diastolic blood pressure; -0.1 mmol/L (-0.2 to 0.1) for glucose; 8% (-3% to 34%) for insulin; -0.3 μg/mL (-1.5 to 0.9) for adiponectin; and 0.0 g/L (-0.1 to 0.1) for apolipoprotein A1. The cluster-adjusted odds ratio for metabolic syndrome, comparing experimental versus control groups, was 1.21 (0.85 to 1.72). CONCLUSIONS An intervention to improve breastfeeding duration and exclusivity among healthy term infants did not influence cardiometabolic risk factors in childhood. CLINICAL TRIAL REGISTRATION Current Controlled Trials: ISRCTN37687716 (http://www.controlled-trials.com/ISRCTN37687716). URL: http://clinicaltrials.gov. Unique identifier: NCT01561612.
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Affiliation(s)
- Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK
- National Institute for Health Research, Bristol Biomedical Research Unit in Nutrition, Bristol, UK
| | - Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Michael S. Kramer
- Departments of Pediatrics and of Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada
| | - Konstantin Vilchuck
- National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Natalia Bogdanovich
- National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Natalia Sergeichick
- National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Nina Gusina
- National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus
| | - Ying Foo
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Tom Palmer
- Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK
| | - Jennifer Thompson
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
| | - Matthew W Gillman
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
| | - George Davey Smith
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Medical Research Council / University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, UK
| | - Emily Oken
- Obesity Prevention Program, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA
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Wynants L, Timmerman D, Bourne T, Van Huffel S, Van Calster B. Screening for data clustering in multicenter studies: the residual intraclass correlation. BMC Med Res Methodol 2013; 13:128. [PMID: 24152372 PMCID: PMC3819732 DOI: 10.1186/1471-2288-13-128] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2013] [Accepted: 09/20/2013] [Indexed: 11/18/2022] Open
Abstract
Background In multicenter studies, center-specific variations in measurements may arise for various reasons, such as low interrater reliability, differences in equipment, deviations from the protocol, sociocultural characteristics, and differences in patient populations due to e.g. local referral patterns. The aim of this research is to derive measures for the degree of clustering. We present a method to detect heavily clustered variables and to identify physicians with outlying measurements. Methods We use regression models with fixed effects to account for patient case-mix and a random cluster intercept to study clustering by physicians. We propose to use the residual intraclass correlation (RICC), the proportion of residual variance that is situated at the cluster level, to detect variables that are influenced by clustering. An RICC of 0 indicates that the variance in the measurements is not due to variation between clusters. We further suggest, where appropriate, to evaluate RICC in combination with R2, the proportion of variance that is explained by the fixed effects. Variables with a high R2 may have benefits that outweigh the disadvantages of clustering in terms of statistical analysis. We apply the proposed methods to a dataset collected for the development of models for ovarian tumor diagnosis. We study the variability in 18 tumor characteristics collected through ultrasound examination, 4 patient characteristics, and the serum marker CA-125 measured by 40 physicians on 2407 patients. Results The RICC showed large variation between variables: from 2.2% for age to 25.1% for the amount of fluid in the pouch of Douglas. Seven variables had an RICC above 15%, indicating that a considerable part of the variance is due to systematic differences at the physician level, rather than random differences at the patient level. Accounting for differences in ultrasound machine quality reduced the RICC for a number of blood flow measurements. Conclusions We recommend that the degree of data clustering is addressed during the monitoring and analysis of multicenter studies. The RICC is a useful tool that expresses the degree of clustering as a percentage. Specific applications are data quality monitoring and variable screening prior to the development of a prediction model.
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Affiliation(s)
| | | | | | | | - Ben Van Calster
- KU Leuven Department of Development and Regeneration, Leuven, Belgium.
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20
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Oken E, Patel R, Guthrie LB, Vilchuck K, Bogdanovich N, Sergeichick N, Palmer TM, Kramer MS, Martin RM. Effects of an intervention to promote breastfeeding on maternal adiposity and blood pressure at 11.5 y postpartum: results from the Promotion of Breastfeeding Intervention Trial, a cluster-randomized controlled trial. Am J Clin Nutr 2013; 98:1048-56. [PMID: 23945719 PMCID: PMC3778859 DOI: 10.3945/ajcn.113.065300] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Accepted: 07/09/2013] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Differences between mothers who do and do not succeed in breastfeeding are likely to confound associations of lactation with later maternal adiposity. OBJECTIVE We compared adiposity and blood pressure (BP) in women randomly assigned to an intervention to promote prolonged and exclusive breastfeeding or usual care. DESIGN We performed a cluster-randomized trial at 31 hospitals in Belarus in 1996-1997. RESULTS Of 17,046 women enrolled at delivery, we assessed 11,867 women (69.6%) at 11.5 y postpartum. The prevalence of exclusive breastfeeding ≥3 mo was 44.5% in 6321 women in the intervention group and 7.1% in 5546 women in the control group. At 11.5 y postpartum, mean (±SD) body mass index (BMI; in kg/m(2)) was 26.5 ± 5.5, the percentage of body fat was 33.6% ± 8.3%, and systolic BP was 124.6 ± 14.6 mm Hg. On intention-to-treat analysis (without imputation) with adjustment for clustering by hospital, mean outcomes were lower in intervention compared with control mothers for BMI (mean difference: -0.27; 95% CI: -0.91, 0.37), body fat (-0.49%; 95% CI: -1.25%, 0.27%), and systolic BP (-0.81 mm Hg; 95% CI: -3.33, 1.71 mm Hg), but effect sizes were small, CIs were wide, and results were attenuated further toward the null after adjustment for baseline characteristics. Results were similar in sensitivity analyses [ie, by using conventional observational analyses disregarding treatment assignment, instrumental variable analyses to estimate the causal effect of breastfeeding, and multiple imputation to account for missing outcome measures (n = 17,046)]. CONCLUSION In women who initiated breastfeeding, an intervention to promote longer breastfeeding duration did not result in an important lowering of adiposity or BP. This trial was registered at clinicaltrials.gov as NCT01561612 and at Current Controlled Trials as ISRCTN37687716.
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Affiliation(s)
- Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA and the Medical Research Council/University of Bristol Integrated Epidemiology Unit, University of Bristol, Bristol, United Kingdom
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21
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Kusuda S, Fujimura M, Uchiyama A, Nakanishi H, Totsu S. Identification of practices and morbidities affecting the mortality of very low birth weight infants using a multilevel logistic analysis: clinical trial or standardisation? BMJ Open 2013; 3:e003317. [PMID: 23970432 PMCID: PMC3753512 DOI: 10.1136/bmjopen-2013-003317] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVES To determine the feasibility of clinical trials of newly developed treatments or standardisation of existing practices to further improve outcomes among very low birth weight (VLBW) infants, a nationwide database was analysed with a two-dimensional approach using two multivariate logistic models. DESIGN Retrospective observational analysis. SETTING Level III perinatal centres in Japan. PARTICIPANTS 15 920 VLBW infants admitted at 38 participating centres from 2003 through 2010. OUTCOME MEASURES Clinical information for the infants was collected until discharge from the centres. A multivariate logistic model identified practices and morbidities associated with mortality. Then, those which were significantly associated with mortality were analysed using a multilevel logistic model. The residues calculated by the multilevel analysis were used as an indicator of centre variation. RESULTS Among practices, antenatal steroids and intubation at birth showed relatively high centre variations (0.9 and 0.8) and favourable ORs (0.7 and 0.5) for mortality, while caesarean section showed a low centre variation (0.4) and a favourable OR (0.8). Sepsis and air leak showed high centre variations (0.4 and 0.4) and high ORs (3.8 and 3.4) among morbidities. Pulmonary haemorrhage, persistent pulmonary hypertension of the newborn, and intraventricular haemorrhage showed moderate variations (0.2, 0.3 and 0.2, respectively) and high ORs (5.6, 4.1 and 2.9, respectively). In contrast, necrotising enterocolitis showed the lowest variation (0.1) and a high OR (4.9). CONCLUSIONS The two-dimensional approach has clearly demonstrated the importance of clinical trial or standardisation. The practices and morbidities with low centre variations and high ORs for mortality must be improved through clinical trials of newly introduced techniques, while standardisation must be considered for practices and morbidities with a high centre variation. TRIAL REGISTRATION The database was registered as UMIN000006961.
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Affiliation(s)
- Satoshi Kusuda
- Department of Neonatal Medicine, Maternal and Perinatal Center, Tokyo Women's Medical University, Tokyo, Japan
| | - Masanori Fujimura
- Department of Neonatology, Osaka Medical Center and Research Institute for Maternal and Child Health, Izumi, Osaka, Japan
| | - Atsushi Uchiyama
- Department of Neonatology, Osaka Medical Center and Research Institute for Maternal and Child Health, Izumi, Osaka, Japan
| | - Hidehiko Nakanishi
- Department of Neonatology, Osaka Medical Center and Research Institute for Maternal and Child Health, Izumi, Osaka, Japan
| | - Satsuki Totsu
- Department of Neonatology, Osaka Medical Center and Research Institute for Maternal and Child Health, Izumi, Osaka, Japan
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22
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Cornu C, Binquet C, Thalamas C, Vigouroux C, Gaillard S, Ginhoux T, Vaz B, Jossan C, Félin A, Sailly A, Gueyffier F, Journot V, Kassaï B. [Public clinical trials: which kind of monitoring should be used?]. Therapie 2013; 68:135-41. [PMID: 23886457 DOI: 10.2515/therapie/2013032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Accepted: 04/04/2013] [Indexed: 11/20/2022]
Abstract
OBJECTIVE Sponsors must take responsibility for the quality of trials at the best possible cost. Our objective was to describe the most frequent quality failures, how they impact trial results, and identify the most efficient monitoring strategies using published articles and reports. RESULTS Errors affecting clinical trials include conception, procedures, data management, and data analysis. The consequences are usually an overestimation of the treatment effect. No study shows that monitoring reduces the risk of errors, and there is no comparison of monitoring methods. Many research organisations advocate for monitoring based on risk analysis and recommend an extensive use of centralised monitoring. CONCLUSIONS Trial quality depends on trial conception and design. Study conduct should guarantee a maximum level of quality level. This should be done using risk management and extensive centralised monitoring.
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23
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Martin RM, Patel R, Kramer MS, Guthrie L, Vilchuck K, Bogdanovich N, Sergeichick N, Gusina N, Foo Y, Palmer T, Rifas-Shiman SL, Gillman MW, Smith GD, Oken E. Effects of promoting longer-term and exclusive breastfeeding on adiposity and insulin-like growth factor-I at age 11.5 years: a randomized trial. JAMA 2013; 309:1005-13. [PMID: 23483175 PMCID: PMC3752893 DOI: 10.1001/jama.2013.167] [Citation(s) in RCA: 125] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Evidence that longer-term and exclusive breastfeeding reduces child obesity risk is based on observational studies that are prone to confounding. OBJECTIVE To investigate effects of an intervention to promote increased duration and exclusivity of breastfeeding on child adiposity and circulating insulin-like growth factor (IGF)-I, which regulates growth. DESIGN, SETTING, AND PARTICIPANTS Cluster-randomized controlled trial in 31 Belarusian maternity hospitals and their affiliated clinics, randomized into 1 of 2 groups: breastfeeding promotion intervention (n = 16) or usual practices (n = 15). Participants were 17,046 breastfeeding mother-infant pairs enrolled in 1996 and 1997, of whom 13,879 (81.4%) were followed up between January 2008 and December 2010 at a median age of 11.5 years. INTERVENTION Breastfeeding promotion intervention modeled on the WHO/UNICEF Baby-Friendly Hospital Initiative (World Health Organization/United Nations Children's Fund). MAIN OUTCOME MEASURES Body mass index (BMI), fat and fat-free mass indices (FMI and FFMI), percent body fat, waist circumference, triceps and subscapular skinfold thicknesses, overweight and obesity, and whole-blood IGF-I. Primary analysis was based on modified intention-to-treat (without imputation), accounting for clustering within hospitals and clinics. RESULTS The experimental intervention substantially increased breastfeeding duration and exclusivity when compared with the control (43% vs 6% exclusively breastfed at 3 months and 7.9% vs 0.6% at 6 months). Cluster-adjusted mean differences in outcomes at 11.5 years of age between experimental vs control groups were: 0.19 (95% CI, -0.09 to 0.46) for BMI; 0.12 (-0.03 to 0.28) for FMI; 0.04 (-0.11 to 0.18) for FFMI; 0.47% (-0.11% to 1.05%) for percent body fat; 0.30 cm (-1.41 to 2.01) for waist circumference; -0.07 mm (-1.71 to 1.57) for triceps and -0.02 mm (-0.79 to 0.75) for subscapular skinfold thicknesses; and -0.02 standard deviations (-0.12 to 0.08) for IGF-I. The cluster-adjusted odds ratio for overweight/obesity (BMI ≥ 85th vs <85th percentile) was 1.18 (95% CI, 1.01 to 1.39) and for obesity (BMI ≥ 95th vs <85th percentile) was 1.17 (95% CI, 0.97 to 1.41). CONCLUSIONS AND RELEVANCE Among healthy term infants in Belarus, an intervention that succeeded in improving the duration and exclusivity of breastfeeding did not prevent overweight or obesity, nor did it affect IGF-I levels at age 11.5 years. Breastfeeding has many advantages but population strategies to increase the duration and exclusivity of breastfeeding are unlikely to curb the obesity epidemic. TRIAL REGISTRATION isrctn.org: ISRCTN37687716; and clinicaltrials.gov: NCT01561612.
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Affiliation(s)
- Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, England.
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24
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Patel R, Oken E, Bogdanovich N, Matush L, Sevkovskaya Z, Chalmers B, Hodnett ED, Vilchuck K, Kramer MS, Martin RM. Cohort profile: The promotion of breastfeeding intervention trial (PROBIT). Int J Epidemiol 2013; 43:679-90. [PMID: 23471837 DOI: 10.1093/ije/dyt003] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The PROmotion of Breastfeeding Intervention Trial (PROBIT) is a multicentre, cluster-randomized controlled trial conducted in the Republic of Belarus, in which the experimental intervention was the promotion of increased breastfeeding duration and exclusivity, modelled on the Baby-friendly hospital initiative. Between June 1996 and December 1997, 17,046 mother-infant pairs were recruited during their postpartum hospital stay from 31 maternity hospitals, of which 16 hospitals and their affiliated polyclinics had been randomly assigned to the arm of PROBIT investigating the promotion of breastfeeding and 15 had been assigned to the control arm, in which breastfeeding practices and policies in effect at the time of randomization was continued. Of the mother-infant pairs originally recruited for the study, 16,492 (96.7%) were followed at regular intervals until the infants were 12 months of age (PROBIT I) for the outcomes of breastfeeding duration and exclusivity; gastrointestinal and respiratory infections; and atopic eczema. Subsequently, 13,889 (81.5%) of the children from these mother-infant pairs were followed-up at age 6.5 years (PROBIT II) for anthropometry, blood pressure (BP), behaviour, dental health, cognitive function, asthma and atopy outcomes, and 13,879 (81.4%) children were followed to the age of 11.5 years (PROBIT III) for anthropometry, body composition, BP, and the measurement of fasted glucose, insulin, adiponectin, insulin-like growth factor-I, and apolipoproteins. The trial registration number for Current Controlled Trials is ISRCTN37687716 and that for ClinicalTrials.gov is NCT01561612. Proposals for collaboration are welcome, and enquires about PROBIT should be made to an executive group of the study steering committee (M.S.K., R.M.M., and E.O.). More information, including information about how to access the trial data, data collection documents, and bibliography, is available at the trial website (http://www.bristol.ac.uk/social-community-medicine/projects/probit/).
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Affiliation(s)
- Rita Patel
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Emily Oken
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Natalia Bogdanovich
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Lidia Matush
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Zinaida Sevkovskaya
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Beverley Chalmers
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Ellen D Hodnett
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Konstantin Vilchuck
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Michael S Kramer
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Richard M Martin
- School of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UKSchool of Social and Community Medicine, University of Bristol, Bristol, UK, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, USA, The National Research and Applied Medicine Mother and Child Centre, Minsk, Belarus, Belarussian Ministry of Health, Minsk, Belarus, Department of Obstetrics and Gynaecology and Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada, Lawrence S. Bloomberg Faculty of Nursing, University of Toronto, Ontario, Canada, Departments of Pediatrics & Epidemiology, Biostatistics and Occupational Health, McGill University Faculty of Medicine, Montreal, Canada and MRC Centre for Causal Analyses in Translational Epidemiology (CAiTE), School of Social and Community Medicine, University of Bristol, Bristol, UK
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