1
|
Perry N, Boulton KA, Hodge A, Ong N, Phillips N, Howard K, Raghunandan R, Silove N, Guastella AJ. A psychometric investigation of health-related quality of life measures for paediatric neurodevelopment assessment: Reliability and concurrent validity of the PEDS-QL, CHU-9D, and the EQ-5D-Y. Autism Res 2024; 17:972-988. [PMID: 38597587 DOI: 10.1002/aur.3127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 03/19/2024] [Indexed: 04/11/2024]
Abstract
There is a need for tools that can provide a brief assessment of functioning for children with neurodevelopmental conditions, including health-related quality of life (HR-QoL). This study evaluated the psychometric properties of three commonly used and well known HR-QoL measures in a cohort of children presenting to clinical developmental assessment services. The most common diagnoses received in these assessment services were autism spectrum disorders. Findings showed good internal consistency for the PedsQL and the CHU-9D, but not the EQ-5D-Y. This research also found that the CHU-9D, EQ-5D-Y, and PedsQL correlated with relevant functioning domains assessed by the VABS-III. Overall, the measures showed that children with neurodevelopmental conditions experienced poor HR-QoL. The majority of children (>86%) met cut-off criteria for significant health concerns on the PedsQL. On the EQ-5D-Y and CHU-9D, they showed reduced HR-QoL particularly on domains relating to school and homework, being able to join in activities, looking after self, and doing usual activities. This study supports the use of the CHU-9D and PedsQL in this population to assess and potentially track HR-QoL in a broad neurodevelopment paediatric population.
Collapse
Affiliation(s)
- N Perry
- Clinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - K A Boulton
- Clinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - A Hodge
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
- Child Development Unit, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - N Ong
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
- Child Development Unit, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - N Phillips
- Clinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - K Howard
- Menzies Centre for Health Policy and Economics, Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - R Raghunandan
- Menzies Centre for Health Policy and Economics, Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - N Silove
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
- Child Development Unit, The Children's Hospital at Westmead, Westmead, New South Wales, Australia
| | - A J Guastella
- Clinic for Autism and Neurodevelopment (CAN) Research, Brain and Mind Centre, Children's Hospital Westmead Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
- Child Neurodevelopment and Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| |
Collapse
|
2
|
Pant A, Gribbin S, Machado P, Hodge A, Wasfy JH, Moran L, Marschner S, Chow CK, Zaman S. Ultra-processed foods and incident cardiovascular disease and hypertension in middle-aged women. Eur J Nutr 2024; 63:713-725. [PMID: 38147150 PMCID: PMC10948520 DOI: 10.1007/s00394-023-03297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/28/2023] [Indexed: 12/27/2023]
Abstract
PURPOSE Ultra-processed food (UPF) intake has increased in recent decades, yet limited knowledge of long-term effects on cardiovascular health persists and sex-specific data is scant. We determined the association of UPF intake with incident cardiovascular disease (CVD) and/or hypertension in a population-based cohort of women. METHODS In the Australian Longitudinal Study on Women's Health, women aged 50-55 years were prospectively followed (2001-2016). UPFs were identified using NOVA classification and contribution of these foods to total dietary intake by weight was estimated. Primary endpoint was incident CVD (self-reported heart disease/stroke). Secondary endpoints were self-reported hypertension, all-cause mortality, type 2 diabetes mellitus, and/or obesity. Logistic regression models assessed associations between UPF intake and incident CVD, adjusting for socio-demographic, medical comorbidities, and dietary variables. RESULTS We included 10,006 women (mean age 52.5 ± 1.5; mean UPF intake 26.6 ± 10.2% of total dietary intake), with 1038 (10.8%) incident CVD, 471 (4.7%) deaths, and 4204 (43.8%) hypertension cases over 15 years of follow-up. In multivariable-adjusted models, the highest [mean 42.0% total dietary intake] versus the lowest [mean 14.2% total dietary intake] quintile of UPF intake was associated with higher incident hypertension [odds ratio (OR) 1.39, 95% confidence interval (CI) 1.10-1.74; p = 0.005] with a linear trend (ptrend = 0.02), but not incident CVD [OR 1.22, 95% CI 0.92-1.61; p = 0.16] or all-cause mortality (OR 0.80, 95% CI 0.54-1.20; p = 0.28). Similar results were found after multiple imputations for missing values. CONCLUSION In women, higher UPF intake was associated with increased hypertension, but not incident CVD. These findings may support minimising UPFs within a healthy diet for women.
Collapse
Affiliation(s)
- Anushriya Pant
- Westmead Applied Research Centre and Faculty of Medicine and Health, University of Sydney, Westmead, NSW, 2145, Australia.
| | - Sarah Gribbin
- Department of General Medicine, The Alfred Hospital, Alfred Health, Melbourne, VIC, Australia
| | - Priscila Machado
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Melbourne, VIC, Australia
| | - Jason H Wasfy
- Cardiology Division, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Lisa Moran
- Monash Centre for Health Research and Implementation, Monash University, Melbourne, VIC, Australia
| | - Simone Marschner
- Westmead Applied Research Centre and Faculty of Medicine and Health, University of Sydney, Westmead, NSW, 2145, Australia
| | - Clara K Chow
- Westmead Applied Research Centre and Faculty of Medicine and Health, University of Sydney, Westmead, NSW, 2145, Australia
| | - Sarah Zaman
- Westmead Applied Research Centre and Faculty of Medicine and Health, University of Sydney, Westmead, NSW, 2145, Australia
- Department of Cardiology, Westmead Hospital, Westmead, NSW, Australia
| |
Collapse
|
3
|
Batt NM, Rodrigues B, Bloom S, Sawhney R, George ES, Hodge A, Vootukuru N, McCrae C, Sood S, Roberts SK, Dev A, Bell S, Thompson A, Ryan MC, Kemp W, Gow PJ, Sood S, Nicoll AJ. Metabolic-associated fatty liver disease and hepatocellular carcinoma: a prospective study of characteristics and response to therapy. J Gastroenterol Hepatol 2024. [PMID: 38369382 DOI: 10.1111/jgh.16501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/31/2023] [Accepted: 01/16/2024] [Indexed: 02/20/2024]
Abstract
BACKGROUND AND AIM The rising incidence of hepatocellular carcinoma (HCC) in Australia is related to increasing rates of metabolic-associated fatty liver disease (MAFLD). This study aimed to prospectively characterize the metabolic profile, lifestyle, biometric features, and response to treatment of HCC patients in an Australian population. METHOD Multicenter prospective cohort analysis of newly diagnosed HCC patients at six multidisciplinary team meetings over a 2-year period. RESULTS Three hundred and thirteen (313) newly diagnosed HCC patients with MAFLD (n = 77), MAFLD plus other liver disease (n = 57) (the "mixed" group), and non-MAFLD (n = 179) were included in the study. Alcohol-associated liver disease (ALD) (43%) and MAFLD (43%) were the most common underlying liver diseases. MAFLD-HCC patients were older (73 years vs 67 years vs 63 years), more likely to be female (40% vs 14% vs 20%), less likely to have cirrhosis (69% vs 88% vs 85%), showed higher ECOG, and were less likely to be identified by screening (29% vs 53% vs 45%). Metabolic syndrome was more prevalent in the MAFLD and mixed groups. The severity of underlying liver disease and HCC characteristics were the same across groups. While the MAFLD population self-reported more sedentary lifestyles, reported dietary patterns were no different across the groups. Dyslipidemia was associated with tumor size, and those taking statins had a lower recurrence rate. CONCLUSION Equal to ALD, MAFLD is now the most common underlying liver disease seen in HCC patients in Australia. Future HCC prevention screening and treatment strategies need to take this important group of patients into consideration.
Collapse
Affiliation(s)
- N M Batt
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
| | - B Rodrigues
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
| | - S Bloom
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - R Sawhney
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - E S George
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - A Hodge
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| | - N Vootukuru
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
| | - C McCrae
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
| | - Surbhi Sood
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - S K Roberts
- Department of Gastroenterology, Alfred Health, Melbourne, Victoria, Australia
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - A Dev
- Department of Gastroenterology, Monash Health, Clayton, Victoria, Australia
| | - S Bell
- Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Gastroenterology, Monash Health, Clayton, Victoria, Australia
| | - A Thompson
- Department of Gastroenterology, St Vincent's Hospital, Fitzroy, Victoria, Australia
- University of Melbourne, Parkville, Victoria, Australia
| | - M C Ryan
- Department of Gastroenterology, St Vincent's Hospital, Fitzroy, Victoria, Australia
- University of Melbourne, Parkville, Victoria, Australia
| | - W Kemp
- Department of Gastroenterology, Alfred Health, Melbourne, Victoria, Australia
| | - P J Gow
- Department of Gastroenterology, Austin Health, Heidelberg, Victoria, Australia
| | - Siddharth Sood
- Department of Gastroenterology and Hepatology, Melbourne Health, Parkville, Victoria, Australia
| | - A J Nicoll
- Department of Gastroenterology, Eastern Health, Box Hill, Victoria, Australia
- Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia
| |
Collapse
|
4
|
Mizrahi D, Swain CTV, Bruinsma F, Hodge A, Taylor N, Lynch BM. The Relationship Between Psychological Distress and Physical Activity Is Non-linear and Differs by Domain: a Cross-Sectional Study. Int J Behav Med 2023; 30:673-681. [PMID: 36180761 PMCID: PMC9524734 DOI: 10.1007/s12529-022-10130-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND There is increasing evidence for the relationship between physical activity (PA), sedentary behaviour and mental health. Limited data exists on sex-specific associations. We aimed to identify associations between PA dose and domain and television time with psychological distress, including sex-stratified models. METHODS A total of 22,176 adults from the Melbourne Collaborative Cohort Study follow-up 2 cohort (2003-2007) participated in this cross-sectional study. Occupational, household, transport, leisure PA, hours watching television and psychological distress were assessed. Restricted cubic splines were used to examine the relationships between PA domains, television viewing time and psychological distress. RESULTS The relationships between PA and psychological distress were non-linear (p < 0.05) and differed by PA domain. There were dose-dependent, inverse associations between distress with transport (B[95% CI] = -0.39[-0.49, -0.30]) and leisure PA (B[95% CI] = -0.35[-0.46, -0.25]). The effect estimates for transport and leisure PA with distress were larger for women. For household domain, a U-shaped curve with an elongated tail was seen. Median PA was associated with lower distress compared with lower quantities (B[95% CI] = -0.12[-0.22, -0.03]); however, this association was not evident with increasing household PA. There were no clear associations between occupational PA and distress. Higher television viewing was associated with higher distress (B[95% CI] = 0.16[0.02, 0.30]). CONCLUSIONS Increasing PA and reducing television viewing may contribute to reduced psychological distress, particularly in women. Future interventions should incorporate leisure and transport PA and decrease television viewing to assess the impact on mental health.
Collapse
Affiliation(s)
- David Mizrahi
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, Australia
- Prince of Wales Clinical School, UNSW Sydney, Sydney, Australia
| | | | - Fiona Bruinsma
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Natalie Taylor
- School of Population Health, UNSW Sydney, Sydney, Australia
| | - Brigid M Lynch
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia.
| |
Collapse
|
5
|
Riboli E, Beland FA, Lachenmeier DW, Marques MM, Phillips DH, Schernhammer E, Afghan A, Assunção R, Caderni G, Corton JC, de Aragão Umbuzeiro G, de Jong D, Deschasaux-Tanguy M, Hodge A, Ishihara J, Levy DD, Mandrioli D, McCullough ML, McNaughton SA, Morita T, Nugent AP, Ogawa K, Pandiri AR, Sergi CM, Touvier M, Zhang L, Benbrahim-Tallaa L, Chittiboyina S, Cuomo D, DeBono NL, Debras C, de Conti A, El Ghissassi F, Fontvieille E, Harewood R, Kaldor J, Mattock H, Pasqual E, Rigutto G, Simba H, Suonio E, Viegas S, Wedekind R, Schubauer-Berigan MK, Madia F. Carcinogenicity of aspartame, methyleugenol, and isoeugenol. Lancet Oncol 2023; 24:848-850. [PMID: 37454664 DOI: 10.1016/s1470-2045(23)00341-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Affiliation(s)
- Elio Riboli
- International Agency for Research on Cancer, Lyon, France
| | | | | | | | | | | | - Abdul Afghan
- International Agency for Research on Cancer, Lyon, France
| | | | | | | | | | - Daphne de Jong
- International Agency for Research on Cancer, Lyon, France
| | | | - Allison Hodge
- International Agency for Research on Cancer, Lyon, France
| | - Junko Ishihara
- International Agency for Research on Cancer, Lyon, France
| | - Dan D Levy
- International Agency for Research on Cancer, Lyon, France
| | | | | | | | - Takeshi Morita
- International Agency for Research on Cancer, Lyon, France
| | - Anne P Nugent
- International Agency for Research on Cancer, Lyon, France
| | - Kumiko Ogawa
- International Agency for Research on Cancer, Lyon, France
| | - Arun R Pandiri
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Luoping Zhang
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Danila Cuomo
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Aline de Conti
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Rhea Harewood
- International Agency for Research on Cancer, Lyon, France
| | - John Kaldor
- International Agency for Research on Cancer, Lyon, France
| | - Heidi Mattock
- International Agency for Research on Cancer, Lyon, France
| | - Elisa Pasqual
- International Agency for Research on Cancer, Lyon, France
| | | | - Hannah Simba
- International Agency for Research on Cancer, Lyon, France
| | - Eero Suonio
- International Agency for Research on Cancer, Lyon, France
| | - Susana Viegas
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Federica Madia
- International Agency for Research on Cancer, Lyon, France
| |
Collapse
|
6
|
Lane MM, Lotfalian M, Hodge A, O'Neil A, Travica N, Jacka FN, Rocks T, Machado P, Forbes M, Ashtree DN, Marx W. High ultra-processed food consumption is associated with elevated psychological distress as an indicator of depression in adults from the Melbourne Collaborative Cohort Study. J Affect Disord 2023; 335:57-66. [PMID: 37149054 DOI: 10.1016/j.jad.2023.04.124] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 04/14/2023] [Accepted: 04/29/2023] [Indexed: 05/08/2023]
Abstract
BACKGROUND Few studies have tested longitudinal associations between ultra-processed food consumption and depressive outcomes. As such, further investigation and replication are necessary. The aim of this study is to examine associations of ultra-processed food intake with elevated psychological distress as a marker for depression after 15 years. METHOD Data from the Melbourne Collaborative Cohort Study (MCCS) were analysed (n = 23,299). We applied the NOVA food classification system to a food frequency questionnaire (FFQ) to determine ultra-processed food intake at baseline. We categorised energy-adjusted ultra-processed food consumption into quartiles by using the distribution of the dataset. Psychological distress was measured by the ten-item Kessler Psychological Distress Scale (K10). We fitted unadjusted and adjusted logistic regression models to assess the association of ultra-processed food consumption (exposure) with significant psychological distress (outcome and defined as K10 ≥ 20). We fitted additional logistic regression models to determine whether these associations were modified by sex, age and body mass index. RESULTS After adjusting for sociodemographic characteristics and lifestyle and health-related behaviours, participants with the highest relative intake of ultra-processed food were at increased odds of significant psychological distress compared to participants with the lowest intake (aOR: 1.23; 95%CI: 1.10, 1.38, p for trend = 0.001). We found no evidence for an interaction of sex, age and body mass index with ultra-processed food intake. CONCLUSION Higher ultra-processed food intake at baseline was associated with subsequent elevated psychological distress as an indicator of depression at follow-up. Further prospective and intervention studies are necessary to identify possible underlying pathways, specify the precise attributes of ultra-processed food that confer harm, and optimise nutrition-related and public health strategies for common mental disorders.
Collapse
Affiliation(s)
- Melissa M Lane
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia.
| | - Mojtaba Lotfalian
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, 615 St Kilda Rd, Melbourne, VIC 3004, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Adrienne O'Neil
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Nikolaj Travica
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Felice N Jacka
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, VIC, Australia; Black Dog Institute, NSW, Australia; James Cook University, QLD, Australia
| | - Tetyana Rocks
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Priscila Machado
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3220, Australia; Center for Epidemiological Research in Nutrition and Health, University of Sao Paulo, Av. Dr. Arnaldo, 715, Sao Paulo 01246-904, Brazil
| | - Malcolm Forbes
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia; Mental Health, Drugs & Alcohol Service, University Hospital Geelong, Barwon Health, VIC 3220, Australia; Department of Psychiatry, University of Melbourne, Parkville, VIC 3050, Australia
| | - Deborah N Ashtree
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| | - Wolfgang Marx
- Deakin University, IMPACT (the Institute for Mental and Physical Health and Clinical Translation), Food & Mood Centre, School of Medicine, Barwon Health, Geelong, Australia
| |
Collapse
|
7
|
O'Connor H, Li S, Hodge A, Callaway L, David Mclntyre H, Barrett H, Wilkinson SA, Nitert MD. Gut microbiome composition is similar between pregnant women with excess body fat with healthy and less healthy dietary intake patterns. J Hum Nutr Diet 2022. [PMID: 36471554 DOI: 10.1111/jhn.13123] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Dietary composition influences the composition of the gut microbiota in healthy adults. Little is known about the effect of dietary patterns on gut microbiota composition in pregnancy. This cross-sectional study aimed to investigate the associations between two diet quality scores adapted from the Australian Recommended Food Score (ARFS) and the Mediterranean Dietary Score (MDS) with the composition of the gut microbiota in pregnant women with excess body fat at 28 weeks' gestation. METHODS Women from the Study of Probiotics IN Gestational diabetes (SPRING) who had completed a food frequency questionnaire (FFQ; n = 395) were classified according to tertiles of ARFS and the MDS. Higher dietary pattern scores in both the ARFS and the MDS represent better diet quality. Gut microbiota composition was assessed using 16S rRNA gene amplicon sequencing and analysed using MicrobiomeAnalyst in a subset of 196 women with faecal samples. RESULTS No significant difference was found in alpha or beta diversity. A higher ARFS was associated with a higher abundance of Ruminococcus and lower abundance of Akkermansia, whereas a higher MDS was associated with a higher abundance of Ruminococcus and Butyricicoccus, though these changes disappeared after correction for multiple testing. CONCLUSION These results suggest that dietary patterns defined by the ARFS and MDS were not associated with gut microbiota composition in pregnant women classified as overweight and obese at 28 weeks' gestation within this study.
Collapse
Affiliation(s)
- Hannah O'Connor
- School of Human Movement and Nutrition Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Sherly Li
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.,MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge Biomedical Campus, University of Cambridge School of Clinical Medicine, Cambridge, UK.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Leonie Callaway
- Women's and Newborns, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.,Faculty of Medicine, The University of Queensland, St Lucia, Queensland, Australia.,Mater Research Institute, The University of Queensland, South Brisbane, Queensland, Australia
| | - Harold David Mclntyre
- Mater Research Institute, The University of Queensland, South Brisbane, Queensland, Australia
| | - Helen Barrett
- Mater Research Institute, The University of Queensland, South Brisbane, Queensland, Australia
| | - Shelley A Wilkinson
- School of Human Movement and Nutrition Sciences, The University of Queensland, St Lucia, Queensland, Australia
| | - Marloes Dekker Nitert
- School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Queensland, Australia
| |
Collapse
|
8
|
Fiorito G, Pedron S, Ochoa-Rosales C, McCrory C, Polidoro S, Zhang Y, Dugué PA, Ratliff S, Zhao WN, McKay GJ, Costa G, Solinas MG, Harris KM, Tumino R, Grioni S, Ricceri F, Panico S, Brenner H, Schwettmann L, Waldenberger M, Matias-Garcia PR, Peters A, Hodge A, Giles GG, Schmitz LL, Levine M, Smith JA, Liu Y, Kee F, Young IS, McGuinness B, McKnight AJ, van Meurs J, Voortman T, Kenny RA, Vineis P, Carmeli C. The Role of Epigenetic Clocks in Explaining Educational Inequalities in Mortality: A Multicohort Study and Meta-analysis. J Gerontol A Biol Sci Med Sci 2022; 77:1750-1759. [PMID: 35172329 PMCID: PMC10310990 DOI: 10.1093/gerona/glac041] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Indexed: 11/13/2022] Open
Abstract
Educational inequalities in all-cause mortality have been observed for decades. However, the underlying biological mechanisms are not well known. We aimed to assess the role of DNA methylation changes in blood captured by epigenetic clocks in explaining these inequalities. Data were from 8 prospective population-based cohort studies, representing 13 021 participants. First, educational inequalities and their portion explained by Horvath DNAmAge, Hannum DNAmAge, DNAmPhenoAge, and DNAmGrimAge epigenetic clocks were assessed in each cohort via counterfactual-based mediation models, on both absolute (hazard difference) and relative (hazard ratio) scales, and by sex. Second, estimates from each cohort were pooled through a random effect meta-analysis model. Men with low education had excess mortality from all causes of 57 deaths per 10 000 person-years (95% confidence interval [CI]: 38, 76) compared with their more advantaged counterparts. For women, the excess mortality was 4 deaths per 10 000 person-years (95% CI: -11, 19). On the relative scale, educational inequalities corresponded to hazard ratios of 1.33 (95% CI: 1.12, 1.57) for men and 1.15 (95% CI: 0.96, 1.37) for women. DNAmGrimAge accounted for the largest proportion, approximately 50%, of the educational inequalities for men, while the proportion was negligible for women. Most of this mediation was explained by differential effects of unhealthy lifestyles and morbidities of the World Health Organization (WHO) risk factors for premature mortality. These results support DNA methylation-based epigenetic aging as a signature of educational inequalities in life expectancy emphasizing the need for policies to address the unequal social distribution of these WHO risk factors.
Collapse
Affiliation(s)
- Giovanni Fiorito
- Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, School of Public Health, Imperial College
London, London, UK
| | - Sara Pedron
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
- Professorship of Public Health and Prevention, Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Centro de Vida Saludable de la Universidad de Conceptión, Conceptiòn, Chile
| | - Cathal McCrory
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | | | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Munich, Germany
| | - Pierre-Antoine Dugué
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Scott Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Wei N Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Gareth J McKay
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Giuseppe Costa
- Epidemiology Unit, Regional Health Service TO3, Grugliasco, Italy
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | | | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7), Ragusa, Italy
| | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Fulvio Ricceri
- Epidemiology Unit, Regional Health Service TO3, Grugliasco, Italy
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, University of Naples Federico II, Naples, Italy
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Munich, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Lars Schwettmann
- Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
- Department of Economics, Martin Luther University, Halle-Wittenberg, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Pamela R Matias-Garcia
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Victoria, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Lauren L Schmitz
- Robert M. La Follette School of Public Affairs, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Morgan Levine
- Department of Pathology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Jennifer A Smith
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, School of Medicine, Duke University, Durham, North Carolina, USA
| | - Frank Kee
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Ian S Young
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | | | - Amy Jayne McKnight
- Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
| | - Joyce van Meurs
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Rose A Kenny
- Department of Medical Gerontology, Trinity College Dublin, Dublin, Ireland
| | | | - Paolo Vineis
- MRC Centre for Environment and Health, School of Public Health, Imperial College
London, London, UK
| | - Cristian Carmeli
- Population Health Laboratory, University of Fribourg, Fribourg, Switzerland
| |
Collapse
|
9
|
Mizrahi D, Swain CT, Bruinsma F, Hodge A, Taylor N, Lynch BM. Physical Activity Domains, Television Viewing Time, Mental Wellbeing And Psychological Distress. Med Sci Sports Exerc 2022. [DOI: 10.1249/01.mss.0000878184.39433.61] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
|
10
|
Wang SE, Hodge A, Dashti SG, Dixon-Suen SC, Castaño-Rodríguez N, Thomas R, Giles G, Boussioutas A, Kendall B, English DR. Diet and risk of Barrett's oesophagus: Melbourne collaborative cohort study. Br J Nutr 2022; 129:1-10. [PMID: 35837679 PMCID: PMC10011587 DOI: 10.1017/s0007114522002112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 06/29/2022] [Accepted: 07/04/2022] [Indexed: 11/08/2022]
Abstract
Barrett's oesophagus (BE) is the precursor of oesophageal adenocarcinoma, which has become the most common type of oesophageal cancer in many Western populations. Existing evidence on diet and risk of BE predominantly comes from case-control studies, which are subject to recall bias in measurement of diet. We aimed to investigate the potential effect of diet, including macronutrients, carotenoids, food groups, specific food items, beverages and dietary scores, on risk of BE in over 20 000 participants of the Melbourne Collaborative Cohort Study. Diet at baseline (1990-1994) was measured using a food frequency questionnaire. The outcome was BE diagnosed between baseline and follow-up (2007-2010). Logistic regression models were used to estimate OR and 95 % CI for diet in relation to risk of BE. Intakes of leafy vegetables and fruit were inversely associated with risk of BE (highest v. lowest quartile: OR = 0·59; CI: 0·38, 0·94; P-trend = 0·02 and OR = 0·58; CI: 0·37, 0·93; P-trend = 0·02 respectively), as were dietary fibre and carotenoids. Stronger associations were observed for food than the nutrients found in them. Positive associations were observed for discretionary food (OR = 1·54; CI: 0·97, 2·44; P-trend = 0·04) and total fat intake (OR per 10 g/d = 1·11; CI: 1·00, 1·23), the association for fat was less robust in sensitivity analyses. No association was observed for meat, protein, dairy products or diet scores. Diet is a potential modifiable risk factor for BE. Public health and clinical guidelines that incorporate dietary recommendations could contribute to reduction in risk of BE and, thereby, oesophageal adenocarcinoma.
Collapse
Affiliation(s)
- Sabrina E. Wang
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Allison Hodge
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - S Ghazaleh Dashti
- Clinical Epidemiology and Biostatistics Unit, Murdoch Children’s Research Institute, Melbourne, VIC, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Suzanne C. Dixon-Suen
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia
| | - Natalia Castaño-Rodríguez
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, NSW, Australia
| | - Robert Thomas
- Department of Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Graham Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Alex Boussioutas
- Department of Gastroenterology, The Alfred, Melbourne, VIC, Australia
- Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Bradley Kendall
- Department of Medicine, The University of Queensland, Brisbane, QLD, Australia
- Department of Gastroenterology and Hepatology, Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Dallas R. English
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
| |
Collapse
|
11
|
Lai HT, Imamura F, Korat AVA, Murphy RA, Tintle N, Bassett JK, Chen J, Kröger J, Chien KL, Senn M, Wood AC, Forouhi NG, Schulze MB, Harris WS, Vasan RS, Hu F, Giles GG, Hodge A, Djousse L, Brouwer IA, Qian F, Sun Q, Wu JH, Marklund M, Lemaitre RN, Siscovick DS, Fretts AM, Shadyab AH, Manson JE, Howard BV, Robinson JG, Wallace RB, Wareham NJ, Chen YDI, Rotter JI, Tsai MY, Micha R, Mozaffarian D. Trans Fatty Acid Biomarkers and Incident Type 2 Diabetes: Pooled Analysis of 12 Prospective Cohort Studies in the Fatty Acids and Outcomes Research Consortium (FORCE). Diabetes Care 2022; 45:854-863. [PMID: 35142845 PMCID: PMC9114723 DOI: 10.2337/dc21-1756] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 01/10/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Trans fatty acids (TFAs) have harmful biologic effects that could increase the risk of type 2 diabetes (T2D), but evidence remains uncertain. We aimed to investigate the prospective associations of TFA biomarkers and T2D by conducting an individual participant-level pooled analysis. RESEARCH DESIGN AND METHODS We included data from an international consortium of 12 prospective cohorts and nested case-control studies from six nations. TFA biomarkers were measured in blood collected between 1990 and 2008 from 25,126 participants aged ≥18 years without prevalent diabetes. Each cohort conducted de novo harmonized analyses using a prespecified protocol, and findings were pooled using inverse-variance weighted meta-analysis. Heterogeneity was explored by prespecified between-study and within-study characteristics. RESULTS During a mean follow-up of 13.5 years, 2,843 cases of incident T2D were identified. In multivariable-adjusted pooled analyses, no significant associations with T2D were identified for trans/trans-18:2, relative risk (RR) 1.09 (95% CI 0.94-1.25); cis/trans-18:2, 0.89 (0.73-1.07); and trans/cis-18:2, 0.87 (0.73-1.03). Trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated with T2D (RR 0.81 [95% CI 0.67-0.99], 0.86 [0.75-0.99], and 0.84 [0.74-0.96], respectively). Findings were not significantly different according to prespecified sources of potential heterogeneity (each P ≥ 0.1). CONCLUSIONS Circulating individual trans-18:2 TFA biomarkers were not associated with risk of T2D, while trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated. Findings may reflect the influence of mixed TFA sources (industrial vs. natural ruminant), a general decline in TFA exposure due to policy changes during this period, or the relatively limited range of TFA levels.
Collapse
Affiliation(s)
- Heidi T.M. Lai
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
- Department of Primary Care and Public Health, Imperial College London, London, U.K
| | - Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K
| | - Andres V. Ardisson Korat
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Rachel A. Murphy
- School of Population & Public Health, Faculty of Medicine, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt University, Sioux Center, IA
- Fatty Acid Research Institute, Sioux Falls, SD
| | - Julie K. Bassett
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Jiaying Chen
- Division of Aging, Brigham and Women's Hospital, Boston, MA
| | - Janine Kröger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Republic of China
| | - Mackenzie Senn
- U.S. Department of Agriculture/Agriculture Research Service Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Alexis C. Wood
- U.S. Department of Agriculture/Agriculture Research Service Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - William S. Harris
- Fatty Acid Research Institute, Sioux Falls, SD
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD
| | - Ramachandran S. Vasan
- Boston University School of Medicine, Boston, MA
- The Framingham Heart Study, Framingham, MA
| | - Frank Hu
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Graham G. Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Luc Djousse
- Divisions of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Ingeborg A. Brouwer
- Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Frank Qian
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Qi Sun
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Jason H.Y. Wu
- The George Institute for Global Health, the Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Matti Marklund
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
- The George Institute for Global Health, the Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | | | - Amanda M. Fretts
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Aladdin H. Shadyab
- Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Barbara V. Howard
- Georgetown University Medical Center, Georgetown University, Hyattsville, MD
| | | | | | - Nick J. Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | | |
Collapse
|
12
|
Hariharan R, Odjidja EN, Scott D, Shivappa N, Hébert JR, Hodge A, de Courten B. The dietary inflammatory index, obesity, type 2 diabetes, and cardiovascular risk factors and diseases. Obes Rev 2022; 23:e13349. [PMID: 34708499 DOI: 10.1111/obr.13349] [Citation(s) in RCA: 77] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 08/15/2021] [Accepted: 08/15/2021] [Indexed: 12/19/2022]
Abstract
An unhealthy diet is a recognized risk factor in the pathophysiology of numerous chronic noncommunicable diseases (NCD), including obesity, type 2 diabetes (T2DM), and cardiovascular diseases (CVD). This is, at least in part, due to unhealthy diets causing chronic low-grade inflammation in the gut and systemically. To characterize the inflammatory potential of diet, we developed the Dietary Inflammatory Index (DII®). Following this development, around 500 papers have been published, which examined the association between the DII, energy-adjusted DII (E-DII™), and the children's DII (C-DII™) and many chronic NCDs including obesity and cardiometabolic diseases. Although a previous narrative review published in 2019 briefly summarized the evidence in this area, there was a significant increase in papers on this topic since 2020. Therefore, the purpose of this narrative review is to provide an in-depth updated review by including all papers until July 2021 on DII and its relationship with obesity, T2DM, and CVD. Furthermore, we aim to identify potential gaps in the literature and provide future directions for research. Most studies found that DII was associated with an increased risk of obesity, T2DM, and CVD with some relationships being sex-specific. However, we identified the paucity of papers describing associations between dietary inflammation and T2DM and its risk factors. Few studies used gold-standard measures of cardiometabolic risk factors. We also identified the lack of interventional studies designed to change the inflammatory potential of diets and study its effect on cardiometabolic risk factors and diseases. We recommend that such interventional studies are needed to assess if changes in DII, representing the inflammatory potential of diet, independently of changes in body composition can modulate cardiometabolic risk factors and diseases.
Collapse
Affiliation(s)
- Rohit Hariharan
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Emmanuel Nene Odjidja
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - David Scott
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia.,Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Nitin Shivappa
- Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.,Department of Nutrition, Connecting Health Innovations LLC, Columbia, South Carolina, USA
| | - James R Hébert
- Cancer Prevention and Control Program and Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA.,Department of Nutrition, Connecting Health Innovations LLC, Columbia, South Carolina, USA
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Barbora de Courten
- Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| |
Collapse
|
13
|
Dyson R, Charman N, Hodge A, Rowe SM, Taylor LF. A survey of mastitis pathogens including antimicrobial susceptibility in southeastern Australian dairy herds. J Dairy Sci 2021; 105:1504-1518. [PMID: 34955276 DOI: 10.3168/jds.2021-20955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 10/23/2021] [Indexed: 12/18/2022]
Abstract
The objectives for this study were to (1) describe the pathogen profile in quarters from cows with clinical mastitis and in cows with subclinical mastitis in southeastern Australia; and (2) describe antimicrobial susceptibility among isolated pathogens. As a secondary objective, we aimed to compare antimicrobial resistance prevalence in pathogens isolated from clinical and subclinical mastitis samples. A convenience sample of dairy herds (n = 65) from 4 regions in southeastern Australia (Gippsland, Northern Victoria, Tasmania, Western Victoria) were invited to submit milk samples from cows with clinical and subclinical mastitis over a 14-mo period (January 2011 to March 2012). Farmers were instructed to collect aseptic quarter milk samples from the first 10 cases of clinical mastitis for each month of the study. In addition, farmers submitted composite milk samples from cows with subclinical mastitis at 1 or 2 sampling occasions during the study period. Aerobic culture and biochemical tests were used to identify isolates. Isolates were classified as susceptible, intermediate, or resistant to a panel of antimicrobial agents based on the zone of growth inhibition around antimicrobial-impregnated disks, with antimicrobial resistance (AMR) classified as nonsusceptibility by combining intermediate and resistant groups into a single category. Generalized linear mixed models were used to compare the prevalence of AMR between clinical and subclinical mastitis isolates. For clinical mastitis samples (n = 3,044), 472 samples (15.5%) were excluded for contamination. Of the remaining samples (n = 2,572), the most common results were Streptococcus uberis (39.2%), no growth (27.5%), Staphylococcus aureus (10.6%), Escherichia coli (8.4%), and Streptococcus dysgalactiae (6.4%). For subclinical mastitis samples (n = 1,072), 425 (39.6%) were excluded due to contamination. Of the remaining samples (n = 647), the most common results were no growth (29.1%), Staph. aureus (29.1%), and Strep. uberis (21.6%). The prevalence of AMR among common isolates was low for the majority of antimicrobial agents. Exploratory analysis found that the probability of Staph. aureus demonstrating resistance to penicillin was 5.16 times higher (95% confidence interval: 1.68, 15.88) in subclinical isolates relative to clinical Staph. aureus isolates. A similar association was observed for amoxicillin with subclinical Staph. aureus isolates being 4.70 times (95% confidence interval: 1.49, 14.75) more likely to be resistant than clinical Staph. aureus isolates. We concluded that the most common bacteria causing clinical mastitis in dairy herds in Australia is likely to be Strep. uberis, whereas Staph. aureus is likely to be the most common cause of subclinical mastitis. Despite decades of antimicrobial use to control these organisms, AMR appears to be uncommon.
Collapse
Affiliation(s)
- R Dyson
- Dairy Focus, 181 Wharparilla Drive, Echuca, Victoria, 3564, Australia
| | - N Charman
- Zoetis Australia, 5 Rider Blvd, Rhodes, New South Wales, 2138, Australia
| | - A Hodge
- Zoetis Australia, 5 Rider Blvd, Rhodes, New South Wales, 2138, Australia
| | - S M Rowe
- Faculty of Science, Sydney School of Veterinary Science, The University of Sydney, Camden, New South Wales 2570, Australia
| | - L F Taylor
- Zoetis Australia, 5 Rider Blvd, Rhodes, New South Wales, 2138, Australia.
| |
Collapse
|
14
|
Bingham CM, Hodge A. Lamb mortality and clostridial disease. N Z Vet J 2021; 70:49-54. [PMID: 34499591 DOI: 10.1080/00480169.2021.1978897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
AIMS To determine the level and timing of lamb loss that occurs during the first year of life on a typical hill country sheep and beef farm in the central North Island of New Zealand and to determine how much of this loss can be prevented through vaccination against the five main clostridial diseases using a commercially available multivalent clostridial vaccine. METHODS The study was conducted on a single commercial hill country sheep and beef farm in the central North Island of New Zealand, with a history of never vaccinating their stock against clostridial disease. Lambs were blocked on sex and randomly selected at docking into treatment (n = 1,705 lambs) and control (n = 1,709 lambs) groups. Treated lambs were vaccinated at docking and 4 weeks later with 1 mL of multivalent clostridial vaccine. Control lambs were not vaccinated. Different coloured ear tags were used to identify the lambs in the treatment and control groups. All lambs were counted at docking (October 2019) and at six other management event times between docking and when the replacement hoggets were set stocked for lambing (August 2020). The number of lambs sold between each management event, from each group was also counted. The difference in the number of lambs from one management event to another, minus the lambs sold between these events was regarded as the lamb losses for that period. RESULTS The total percentage of lamb losses from docking to pre-lamb was 4.8% (81/1,705) and 6.2% (106/1,709) in the vaccinated and unvaccinated lambs respectively OR = 0.75 (95% CI = 0.56-1.02; p = 0.06). Most lamb loss occurred in the period after docking, followed by the period between weaning and the first post-weaning drench. Less lamb loss occurred in the vaccinated lambs (27/1,705; 1.6%) after docking than in the unvaccinated lambs (66/1,709; 3.9%). This was mainly due to lower female lamb losses in the vaccinated (5/868; 0.6%) compared to the unvaccinated (38/868; 4.4%) group (p < 0.001). CONCLUSIONS Vaccination of lambs at docking and 4 weeks later, with a multivalent 5-in-1 clostridial vaccine was associated with a 23.6% (25/106) reduction in total lamb loss from docking to pre-lambing. In female lambs, vaccination was associated with an 87% (33/38) reduction in lamb loss after docking and a 37% (22/59) reduction over the total trial period.
Collapse
Affiliation(s)
- C M Bingham
- Zoetis New Zealand Ltd, Auckland, New Zealand
| | - A Hodge
- Zoetis Veterinary Medicine Research and Development, Rhodes, Australia
| |
Collapse
|
15
|
Wang MS, Dashti G, Hodge A, Kendall B, Dixon-Suen S, Giles G, Milne R, English D. 1210Understanding the effect of Helicobacter pylori infection on gastroesophageal reflux disease and Barrett’s oesophagus. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Helicobacter pylori (H.pylori) infection causes atrophic gastritis and gastric cancer. Ironically, decreased gastric acid production in those with atrophic gastritis might reduce harmful gastroesophageal refluxate, thereby reducing gastroesophageal reflux disease (GERD) and Barrett’s oesophagus (BE) risk.
Methods
In two nested case-control studies with 425 GERD and 169 BE cases, we compared sex-specific GERD and BE risk in H.pylori seronegative participants with seropositive participants. Where seronegativity was associated with increased BE risk, we quantified the effect mediated by GERD using a Monte Carlo simulation-based g-computation approach to estimate interventional effects. Moreover, we classified participants into gastritis types using serum pepsinogen-I and gastrin-17 data.
Results
For men, H.pylori seronegativity was associated with 1.69-fold (CI:1.03-2.75) and 2.14-fold (CI:1.18-3.88) higher odds for GERD and BE respectively. Five (33%) out of the 15 per 1000 excess BE risk from being seronegative was mediated by GERD. No association was observed for women. Among those seropositive, the proportion with atrophic antral gastritis was higher for men than for women (68% vs 56%; p = 0.015).
Conclusions
H.pylori seronegativity was associated with increased GERD and BE risk for men but not women, which could be partly explained by the higher proportion of H.pylori-associated atrophic antral gastritis in men. Evidence of GERD mediating seronegativity’s effect on BE supports this explanation.
Key messages
Whilst H.pylori infection might reduce GERD and BE risk, this is potentially a by-product of atrophic gastritis, a risk factor for gastric cancer. Treating GERD could partly reduce the excess BE risk for seronegative individuals.
Collapse
Affiliation(s)
- Miss Sabrina Wang
- The University Of Melbourne, Parkville, Australia
- Cancer Council Victoria, Melbourne, Australia
| | | | - Allison Hodge
- The University Of Melbourne, Parkville, Australia
- Cancer Council Victoria, Melbourne, Australia
| | | | | | | | - Roger Milne
- The University Of Melbourne, Parkville, Australia
- Cancer Council Victoria, Melbourne, Australia
| | - Dallas English
- The University Of Melbourne, Parkville, Australia
- Cancer Council Victoria, Melbourne, Australia
| |
Collapse
|
16
|
Jayasekara H, MacInnis R, Yang Y, Hodge A, Mitchell H, Haydon A, Room R, Hopper J, Gunter M, Riboli E, Giles G, Milne R, English D, Ferrari P. 783Lifetime alcohol intake and stomach cancer risk: a pooled analysis of two prospective cohort studies. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Alcohol consumption is causally linked to several cancer sites but the evidence for stomach cancer is still inconclusive. We aimed to quantify the association between alcohol intake and risk of stomach cancer, including subtypes.
Methods
We pooled data from two cohort studies including 452,958 individuals enrolled in the European Prospective Investigation into Cancer in 1992-98 and 38,756 Australians enrolled in the Melbourne Collaborative Cohort Study in 1990-94. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) for incident stomach cancer were estimated using Cox regression.
Results
1,225 incident stomach cancers were diagnosed over 7,094,637 person-years. Alcohol intake was not associated with overall stomach cancer risk. We observed a weak positive dose-response association for lifetime intake with non-cardia stomach cancer (HR = 1.03, 95% CI: 1.00-1.06/per 10 g/day increment), which is the more common type (77.6% of cases), and a weak inverse association with cardia cancer (HR = 0.93, 95% CI: 0.87-1.00) (phomogeneity=0.006). These associations did not differ appreciably by smoking or Helicobacter pylori infection status. Differences in HRs between diffuse-type and intestinal-type cancer were minimal (phomogeneity=0.97). HRs of 1.50 (95% CI: 1.12-2.01) for non-cardia and 0.53 (95% CI: 0.27-1.02) for cardia cancer were observed for a life course trajectory characterised by sustained heavy drinking compared with light drinking (phomogeneity=0.01).
Conclusions
Lifetime alcohol intake was associated with increased risk of non-cardia stomach cancer. The inverse association for cardia cancer indicates aetiologic differences between subsites.
Key messages
Limiting long-term alcohol consumption, and avoiding heavy use in particular, might be beneficial in preventing non-cardia stomach cancer.
Collapse
Affiliation(s)
| | - Robert MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Yi Yang
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Hazel Mitchell
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, Australia
| | - Andrew Haydon
- Department of Medical Oncology, Alfred Hospital, Melbourne, Australia
| | - Robin Room
- Centre for Alcohol Policy Research, La Trobe University, Bundoora, Australia
| | - John Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Marc Gunter
- on behalf of EPIC PIs and collaborators, International Agency for Research On Cancer, Lyon, France
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Graham Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Roger Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Dallas English
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - Pietro Ferrari
- on behalf of EPIC PIs and collaborators, International Agency for Research On Cancer, Lyon, France
| |
Collapse
|
17
|
Dugué PA, Hodge A, Wong EM, Joo E, Jung CH, Hopper J, English D, Giles G, Milne R, Southey M. 870Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.
Methods
Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (N = 406 cases), colorectal (N = 814), gastric (N = 166), kidney (N = 139), lung (N = 327), prostate (N = 847) and urothelial cancer (N = 404) and B-cell lymphoma (N = 426). We used conditional logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28, and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting), and methylation scores for personal smoking.
Results
All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential inverse associations were observed with risk of lung cancer and B-cell lymphoma.
Conclusions
We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer.
Key messages
Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.
Collapse
Affiliation(s)
| | | | | | - Eric Joo
- The University of Melbourne, Melbourne, Australia
| | | | - John Hopper
- The University of Melbourne, Melbourne, Australia
| | | | | | - Roger Milne
- Cancer Council Victoria, Melbourne, Australia
| | | |
Collapse
|
18
|
Dugué PA, Hodge A, Ueland P, Midttun Ø, Ulvik A, Rinaldi S, MacInnis R, Li S, Meyer K, Navionis AS, Flicker L, Severi G, English D, Vineis P, Southey M, Milne R, Giles G. 876Association of blood markers of inflammation, vitamin status and the kynurenine pathway with age and all-cause mortality. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Inflammation is a key feature of aging and a cause of numerous diseases. We investigated the association of 35 blood markers involved in inflammatory processes with age and mortality and developed a signature of ‘inflammaging’.
Methods
Thirty-five blood markers relating to the kynurenine pathway, vitamin status, and inflammation were measured in 976 participants in the Melbourne Collaborative Cohort Study at baseline (1990-1994, median age 59 years) and follow-up (2003-2007, median age 70 years). Associations of each marker with age and all-cause mortality were assessed using linear and Cox regression, respectively. A signature of inflammaging was obtained via Lasso regression of age on the markers and tested for association with mortality; we compared mortality associations for this signature and two weighted scores across all markers associated with age and mortality, respectively.
Results
Most markers (29/35) were associated with age, with strongest associations observed for cystatin C, neopterin, quinolinic acid, and the kynurenine/tryptophan ratio, PAr index, and 3-hydroxykynurenine/xanthurenic acid ratio. Many markers (14/35) showed strong associations with mortality in particular neopterin, quinolinic acid, HK/XA, PAr index, CRP, IL-6 and KTr. The inflammaging signature included six markers and showed strong association with mortality (HR = 1.5, 95%CI: 1.3-1.7), almost as strong as the association of weighted scores combining all measured markers.
Conclusions
Our study highlights the key role played by markers of the kynurenine pathway and vitamin B6 catabolism in aging, along with other well-established inflammation-related markers.
Key messages
A signature of ‘inflammaging’ based on 6 markers may be useful to better predict mortality.
Collapse
Affiliation(s)
- Pierre-antoine Dugué
- Monash University, Clayton, Australia
- Cancer Council Victoria, Melbourne, Australia
- The University of Melbourne, Melbourne, Australia
| | | | | | | | | | - Sabina Rinaldi
- International Agency for Research on Cancer, Lyon, France
| | | | - Sherly Li
- Cancer Council Victoria, Melbourne, Australia
| | | | | | - Leon Flicker
- University of Western Australia, Perth, Australia
| | | | | | | | | | - Roger Milne
- Cancer Council Victoria, Melbourne, Australia
| | | |
Collapse
|
19
|
Makama M, Lim S, Hill B, Skouteris H, Teede H, Boyle J, Hodge A, Earnest A, Moran L. 536Patterns of change in lifestyle behaviours following childbirth. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Lifestyle behaviours may worsen following childbirth due to barriers such as time constraints and reduced prioritization of personal health. We therefore aimed to assess the patterns of change in weight and lifestyle behaviours following childbirth in a longitudinal community-based cohort.
Methods
Data from surveys 3 and 5 (ages 25-30 and 31-36 years) of the 1973-8 birth cohort of the Australian Longitudinal Study on Women’s Health were used. We assessed changes in weight, energy intake, diet (diet quality, macronutrients and micronutrients), physical activity and sitting time in parous women compared to those who remained nulliparous by survey 5 using one-way analysis of covariance.
Results
Of 4927 nulliparous women at survey 3, 2503 became parous by survey 5. Over 6 years, parous women had an increase in weight (1 kg; 95%CI 0.50, 1.54), higher energy intake (833.3 kJ/day; 95%CI 706.07, 960.52), better diet quality (1.4 units; 95%CI 0.81, 2.08), lower physical activity (-370.5 METmin/day; 95%CI -427.07, -313.87) and less sitting time (-1.8 hours/day; 95%CI -1.93, -1.60) than nulliparous women on adjusted analyses. On stratification of parity, the improvement in diet quality was only present in primiparous women and sitting time decreased with higher parity.
Conclusion
There is a worsening in weight and some lifestyle behaviours following childbirth in Australian women. While higher parity was associated with further decreases in sitting time, improvements in diet quality were not maintained.
Key message
Women need support to maintain healthy lifestyle behaviours amidst the challenges of caring for children, particularly with increasing family size.
Collapse
Affiliation(s)
- Maureen Makama
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Siew Lim
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Briony Hill
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Helen Skouteris
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Helena Teede
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Jacqueline Boyle
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | | | - Arul Earnest
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia
| | - Lisa Moran
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| |
Collapse
|
20
|
Martin J, Joham A, Mishra G, Hodge A, Moran L, Harrison C. 352Postpartum diet quality: A cross-sectional analysis from the Australian longitudinal study on women’s health. Int J Epidemiol 2021. [DOI: 10.1093/ije/dyab168.454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Reproductive-aged women are at high risk of developing obesity, and diet quality is a potential modifiable risk factor. There is limited research exploring postpartum diet quality.
Methods
Using data from the Australian Longitudinal Study on women’s Health of women, who reported having previously given birth, we investigated the association between time since childbirth and diet quality, and differences in energy, macronutrients, micronutrient intake, and diet quality assessed by the dietary guideline index (DGI) in women stratified by time from last childbirth, early (≤6 months; n = 558) and late (7–12 months; n = 547), and others (>12 months post childbirth; n = 3434).
Results
From this cohort, 4539 participants completed a food frequency questionnaire and were included in this analysis. Overall, diet quality was higher in early and late postpartum women (mean DGI score 89.8±10.5 and 90.0±10.2, respectively) compared to others (>12 months post childbirth), (85.2±11.7; p < 0.001). Factors positively associated with diet quality included higher education, physical activity, health provider support, and vitamin and/or mineral supplement use. Conversely, increasing time from childbirth (>12 months), smoking compared with non-smoking and medium income level compared with no income was negatively associated with diet quality.
Conclusions
A lower diet quality in women >12 months post childbirth may be reflective of increased pressures, balancing childrearing and return to work responsibilities. This highlights the need to support women beyond the postpartum period to improve modifiable factors associated with weight gain, including diet quality, to optimize health and reduce chronic disease risk.
Key messages
Diet quality; nutrition; obesity; prevention; postpartum; reproductive; women
Collapse
Affiliation(s)
- Julie Martin
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventative Medicine, Monash University, Melbourne/Clayton, Australia
| | - Anju Joham
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventative Medicine, Monash University, Melbourne/Clayton, Australia
- Diabetes and Vascular Medicine Unit, Monash Health, Melbourne/Clayton, Australia
| | - Gita Mishra
- Centre for Longitudinal and Life Course Research, School of Public Health, University of Queensland, Brisbane, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Lisa Moran
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventative Medicine, Monash University, Melbourne/Clayton, Australia
| | - Cheryce Harrison
- Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventative Medicine, Monash University, Melbourne/Clayton, Australia
| |
Collapse
|
21
|
Qian F, Ardisson Korat AV, Imamura F, Marklund M, Tintle N, Virtanen JK, Zhou X, Bassett JK, Lai H, Hirakawa Y, Chien KL, Wood AC, Lankinen M, Murphy RA, Samieri C, Pertiwi K, de Mello VD, Guan W, Forouhi NG, Wareham N, Hu ICFB, Riserus U, Lind L, Harris WS, Shadyab AH, Robinson JG, Steffen LM, Hodge A, Giles GG, Ninomiya T, Uusitupa M, Tuomilehto J, Lindström J, Laakso M, Siscovick DS, Helmer C, Geleijnse JM, Wu JHY, Fretts A, Lemaitre RN, Micha R, Mozaffarian D, Sun Q. n-3 Fatty Acid Biomarkers and Incident Type 2 Diabetes: An Individual Participant-Level Pooling Project of 20 Prospective Cohort Studies. Diabetes Care 2021; 44:1133-1142. [PMID: 33658295 PMCID: PMC8132316 DOI: 10.2337/dc20-2426] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 02/04/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Prospective associations between n-3 fatty acid biomarkers and type 2 diabetes (T2D) risk are not consistent in individual studies. We aimed to summarize the prospective associations of biomarkers of α-linolenic acid (ALA), eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA) with T2D risk through an individual participant-level pooled analysis. RESEARCH DESIGN AND METHODS For our analysis we incorporated data from a global consortium of 20 prospective studies from 14 countries. We included 65,147 participants who had blood measurements of ALA, EPA, DPA, or DHA and were free of diabetes at baseline. De novo harmonized analyses were performed in each cohort following a prespecified protocol, and cohort-specific associations were pooled using inverse variance-weighted meta-analysis. RESULTS A total of 16,693 incident T2D cases were identified during follow-up (median follow-up ranging from 2.5 to 21.2 years). In pooled multivariable analysis, per interquintile range (difference between the 90th and 10th percentiles for each fatty acid), EPA, DPA, DHA, and their sum were associated with lower T2D incidence, with hazard ratios (HRs) and 95% CIs of 0.92 (0.87, 0.96), 0.79 (0.73, 0.85), 0.82 (0.76, 0.89), and 0.81 (0.75, 0.88), respectively (all P < 0.001). ALA was not associated with T2D (HR 0.97 [95% CI 0.92, 1.02]) per interquintile range. Associations were robust across prespecified subgroups as well as in sensitivity analyses. CONCLUSIONS Higher circulating biomarkers of seafood-derived n-3 fatty acids, including EPA, DPA, DHA, and their sum, were associated with lower risk of T2D in a global consortium of prospective studies. The biomarker of plant-derived ALA was not significantly associated with T2D risk.
Collapse
Affiliation(s)
- Frank Qian
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.,Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Andres V Ardisson Korat
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - Matti Marklund
- Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.,Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.,The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt University, Sioux Center, IA.,Fatty Acid Research Institute, Sioux Falls, SD
| | - Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Xia Zhou
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | | | - Heidi Lai
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.,Imperial College London, London, U.K
| | - Yoichiro Hirakawa
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.,Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Alexis C Wood
- Children's Nutrition Research Center, U.S. Department of Agriculture/Agricultural Research Service, Houston, TX
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Rachel A Murphy
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Cecilia Samieri
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Kamalita Pertiwi
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
| | - Vanessa D de Mello
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN
| | - Nita G Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - Nick Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - InterAct Consortium Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.,Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Ulf Riserus
- Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Clinical Nutrition and Metabolism, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.,Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - William S Harris
- Fatty Acid Research Institute, Sioux Falls, SD.,Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD
| | - Aladdin H Shadyab
- Department of Family Medicine and Public Health, University of California San Diego School of Medicine, La Jolla, CA
| | | | - Lyn M Steffen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Allison Hodge
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Graham G Giles
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia.,Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Center for Cohort Studies, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Jaakko Tuomilehto
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland.,Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jaana Lindström
- Public Health Promotion Unit, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | | | - Catherine Helmer
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Johanna M Geleijnse
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Jason H Y Wu
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Amanda Fretts
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.,Division of Cardiology, Tufts Medical Center, Boston, MA
| | | | | |
Collapse
|
22
|
Luo J, Hodge A, Hendryx M, Byles JE. BMI trajectory and subsequent risk of type 2 diabetes among middle-aged women. Nutr Metab Cardiovasc Dis 2021; 31:1063-1070. [PMID: 33612383 PMCID: PMC8005471 DOI: 10.1016/j.numecd.2020.12.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/10/2020] [Accepted: 12/12/2020] [Indexed: 01/04/2023]
Abstract
BACKGROUND AND AIMS Little is known about how weight trajectories among women during menopausal transition and beyond may be related to risk of type 2 diabetes mellitus (T2DM). The aim of this study was to examine associations between body mass index (BMI) trajectories over 20 years, age of obesity onset, cumulative obese-years and incidence of T2DM among middle-aged women. METHODS AND RESULTS 12,302 women enrolled in the Australian Longitudinal Study on Women's Health (ALSWH) were surveyed in 1996 (Survey 1, age 45-50), 1998 and then every three years to 2016. Self-reported weight and height were collected for up to eight time points. Incident diabetes was assessed via validated self-report of physician-diagnosed diabetes. Growth mixture models were used to identify distinct BMI trajectories. A total of 1380 (11.2%) women newly developed T2DM over an average 16 years of follow-up. Seven distinct BMI trajectories were identified with differential risk of developing T2DM. Initial BMI was positively associated with T2DM risk. We also observed that risk of T2DM was positively associated with rapid weight increase, early age of obesity onset and greater obese-years. CONCLUSION Slowing down weight increases, delaying the onset of obesity, or reducing cumulative exposure to obesity may substantially lower the risk of developing T2DM.
Collapse
Affiliation(s)
- Juhua Luo
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, USA.
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Michael Hendryx
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, USA
| | - Julie E Byles
- Research Centre for Generational Health and Ageing, University of Newcastle, Newcastle, NSW, Australia
| |
Collapse
|
23
|
Gribbin S, Enticott J, Hodge A, Moran L, Joham A, Thong E, Zaman S. Higher Dietary Carbohydrate Intake and Not Saturated Fat is Inversely Associated With Cardiovascular Disease in Australian Women. Heart Lung Circ 2021. [DOI: 10.1016/j.hlc.2021.06.411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
|
24
|
Bennett C, Mansfield D, Mo L, Hodge A, Joham A, Cain S, Blumfield M, Teede H, Moran LJ. MON-043 Sleep Disturbances in Women with and Without Polycystic Ovary Syndrome (PCOS) and Their Association with Lifestyle Factors (Diet, Physical Activity and Sitting Time). J Endocr Soc 2020. [PMCID: PMC7207944 DOI: 10.1210/jendso/bvaa046.093] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Sleep disturbances in women with and without polycystic ovary syndrome (PCOS) and their association with lifestyle factors (diet, physical activity and sitting time) Bennett C1, Mansfield DR2, Mo L2, Hodge A3, Joham A4, 5, Cain SW6, Blumfield M1, Teede H4, 5, Moran LJ4 1. Be Active Sleep and Eat (BASE) Facility, Department of Nutrition and Dietetics, School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria 2. Monash Lung and Sleep, Monash Health, Clayton, Victoria 3. Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria 4. Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Victoria 5. Diabetes and Vascular Medicine Unit, Monash Health, Clayton, Victoria 6. Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, Victoria Sleep disturbances are a risk factor for poorer lifestyle behaviours. While PCOS is associated with a higher prevalence of sleep disturbances, the relationship between sleep and lifestyle behaviours is unknown in PCOS. Self-reported data from the Australian Longitudinal Study on Women’s Health young cohort (31–36 years, n=6067, n=464 PCOS, n=5603 non-PCOS) were collected on PCOS, anthropometry, physical activity, sedentary behaviour, diet (74-item validated food frequency questionnaire) and sleeping behaviour (sleep quantity and adverse sleep symptoms). Multivariate regression models controlled for sleeping behaviour, BMI, age, marital status, education, income and area of residence. Women with PCOS reported greater adverse sleep symptoms, higher energy intake, diet quality (dietary guidelines index (DGI)), fibre intake and sedentary time and lower glycaemic index, compared to women without PCOS. This was not maintained for energy intake and sedentary behaviour on adjustment for confounders. For diet quality, there was an interaction between PCOS and sleep disturbances. Only for women with fewer sleep disturbances (~8 hours sleep/no adverse sleep symptoms) was PCOS associated with better diet quality (DGI higher by 3.14±0.86, p<0.001), with no differences in diet quality for women with poorer sleep. Lifestyle behaviours in women with PCOS appear to be influenced by sleep quality and quantity. Nothing to disclose: CB, DM, LM, AH, AJ, SC, MB, HT, LM
Collapse
Affiliation(s)
| | | | - Lin Mo
- Monash Health, Melbourne, Australia
| | | | | | - Sean Cain
- Monash University, Melbourne, Australia
| | | | | | | |
Collapse
|
25
|
Hayes E, Hodge A, Meyer E, Nichol K, Deitemyer M, Duffy V, Cotterman C, McLain E, Gajarski R, Nandi D. A Comparison of Intra-Operative Isohemagglutinin Removal Techniques in Pediatric Heart Transplantation. J Heart Lung Transplant 2020. [DOI: 10.1016/j.healun.2020.01.288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
|
26
|
Rayner J, D'Arcy E, Ross LJ, Hodge A, Schoenaker DAJM. Carbohydrate restriction in midlife is associated with higher risk of type 2 diabetes among Australian women: A cohort study. Nutr Metab Cardiovasc Dis 2020; 30:400-409. [PMID: 31822429 DOI: 10.1016/j.numecd.2019.11.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Revised: 10/16/2019] [Accepted: 11/01/2019] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND AIMS Low-carbohydrate diets (LCDs) are increasingly popular but may be nutritionally inadequate. We aimed to examine if carbohydrate restriction in midlife is associated with risk of developing type 2 diabetes (T2DM), and if this association differs by previous gestational diabetes (GDM) diagnosis. METHODS AND RESULTS Dietary intake was assessed for 9689 women from the Australian Longitudinal Study on Women's Health in 2001 (aged 50-55) and 2013 (aged 62-67) via validated food frequency questionnaires. Average long-term carbohydrate restriction was assessed using a low-carbohydrate diet score (highest quartile (Q4) indicating lowest proportion of energy from carbohydrates). Incidence of T2DM between 2001 and 2016 was self-reported at 3-yearly surveys. Log-binomial regression was used to estimate relative risks (RR) and 95% CIs. During 15 years of follow-up, 959 women (9.9%) developed T2DM. Carbohydrate restriction was associated with T2DM after adjustment for sociodemographic factors, history of GDM diagnosis and physical activity (Q4 vs Q1: RR 1.27 [95% CI 1.10, 1.48]), and this was attenuated when additionally adjusted for BMI (1.10 [0.95, 1.27]). Carbohydrate restriction was associated with lower consumption of fruit, cereals and high-fibre bread, and lower intakes of these food groups were associated with higher T2DM risk. Associations did not differ by history of GDM (P for interaction >0.15). CONCLUSION Carbohydrate restriction was associated with higher T2DM incidence in middle-aged women, regardless of GDM history. Health professionals should advise women to avoid LCDs that are low in fruit and grains, and to consume a diet in line with current dietary recommendations.
Collapse
Affiliation(s)
- Jessica Rayner
- Nutrition and Dietetics, School of Allied Health, Griffith University, Queensland, Australia
| | - Ellie D'Arcy
- Nutrition and Dietetics, School of Allied Health, Griffith University, Queensland, Australia; Integrated Primary Care and Partnerships, Western New South Wales Local Health District, NSW, Australia
| | - Lynda J Ross
- Nutrition and Dietetics, School of Allied Health, Griffith University, Queensland, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia
| | - Danielle A J M Schoenaker
- School of Medicine, Faculty of Science, Medicine and Health, and Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW, Australia; The Robinson Research Institute and Discipline of Obstetrics and Gynaecology, University of Adelaide, Adelaide, South Australia, Australia; Centre for Behavioural Research in Cancer, Cancer Council Victoria, Melbourne, Victoria, Australia.
| |
Collapse
|
27
|
Luo J, Hodge A, Hendryx M, Byles JE. Age of obesity onset, cumulative obesity exposure over early adulthood and risk of type 2 diabetes. Diabetologia 2020; 63:519-527. [PMID: 31858184 DOI: 10.1007/s00125-019-05058-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 10/31/2019] [Indexed: 02/08/2023]
Abstract
AIMS/HYPOTHESIS Obesity is a risk factor for type 2 diabetes, yet little is known about how timing and cumulative exposure of obesity are related to disease risk. The aim of this study was to examine the associations between BMI trajectories, age of onset of obesity and obese-years (a product of degree and duration of obesity) over early adulthood and subsequent risk of type 2 diabetes. METHODS Women aged 18-23 years at baseline (n = 11,192) enrolled in the Australian Longitudinal Study on Women's Health (ALSWH) in 1996 were followed up about every 3 years via surveys for up to 19 years. Self-reported weights were collected up to seven times. Incident type 2 diabetes was self-reported. A growth mixture model was used to identify distinct BMI trajectories over the early adult life course. Cox proportional hazards regression models were used to examine the associations between trajectories and risk of diabetes. RESULTS One hundred and sixty-two (1.5%) women were newly diagnosed with type 2 diabetes during a mean of 16 years of follow-up. Six distinct BMI trajectories were identified, varying by different initial BMI and different slopes of increase. Initial BMI was positively associated with risk of diabetes. We also observed that age at onset of obesity was negatively associated with risk of diabetes (HR 0.87 [95% CI 0.79, 0.96] per 1 year increment), and number of obese-years was positively associated with diabetes (p for trend <0.0001). CONCLUSIONS/INTERPRETATION Our data revealed the importance of timing of obesity, and cumulative exposure to obesity in the development of type 2 diabetes in young women, suggesting that preventing or delaying the onset of obesity and reducing cumulative exposure to obesity may substantially lower the risk of developing diabetes.
Collapse
Affiliation(s)
- Juhua Luo
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, 1025 E 7th Street, Bloomington, IN, 47405, USA.
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia
| | - Michael Hendryx
- Department of Environmental and Occupational Health, School of Public Health, Indiana University, Bloomington, IN, USA
| | - Julie E Byles
- Research Centre for Generational Health and Ageing, University of Newcastle, Newcastle, NSW, Australia
| |
Collapse
|
28
|
Grieger JA, Hodge A, Mishra G, Joham AE, Moran LJ. The Association between Dietary Intake, Asthma, and PCOS in Women from the Australian Longitudinal Study on Women's Health. J Clin Med 2020; 9:E233. [PMID: 31952348 PMCID: PMC7019521 DOI: 10.3390/jcm9010233] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 01/06/2020] [Accepted: 01/12/2020] [Indexed: 01/23/2023] Open
Abstract
Dietary intake potentially modifies the prevalence or severity of asthma. The prevalence of asthma is higher in women with polycystic ovary syndrome (PCOS); it is not known if diet confounds or modifies the association between asthma and PCOS. The aims of this study were: (i) To determine if the association of PCOS and asthma is independent of dietary pattern and (ii) to determine if dietary pattern modifies the association between PCOS and asthma. Women in this study were from the Australian Longitudinal Study on Women's Health (ALSWH) cohort born between 1973 to 1978 and aged 18 to 23 years (n = 7382). Logistic regression was used to assess the association between PCOS and asthma, adjusting for the following: (i) Potential confounders identified a priori and (ii) dietary patterns (z-score) identified by principle component analysis. In the adjusted analysis, women with PCOS were more likely to have asthma than the women without PCOS (OR 1.35 and 95% CI, 1.02 and 1.78). This relationship was not altered by further adjustment for dietary patterns (non-core food, meats and takeaway, or Mediterranean-style pattern). In the interaction analysis, only the women consuming less than the median intake of non-core foods (i.e., lower intake of discretionary or unhealthy foods) and with PCOS were more likely to have asthma (OR 1.91 and 95% CI, 1.29 and 2.82). Dietary intake did not confound the relationship between PCOS and asthma. Other mechanistic pathways are likely responsible for the asthma and PCOS association, and further studies assessing factors such as oral contraceptive use and sex steroid hormones warrant investigation.
Collapse
Affiliation(s)
- Jessica A Grieger
- Robinson Research Institute, University of Adelaide, North Adelaide, SA 5005, Australia;
- Adelaide Medical School, University of Adelaide, Adelaide, SA 5005, Australia
| | - Allison Hodge
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VCT 3004, Australia;
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VCT 3010, Australia
| | - Gita Mishra
- School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4072, Australia;
| | - Anju E Joham
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, VCT 3168, Australia;
- Diabetes and Vascular Medicine, Monash Health, Clayton, VCT 3168, Australia
| | - Lisa J Moran
- Robinson Research Institute, University of Adelaide, North Adelaide, SA 5005, Australia;
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, VCT 3168, Australia;
| |
Collapse
|
29
|
Lee CMY, Colagiuri S, Woodward M, Gregg EW, Adams R, Azizi F, Gabriel R, Gill TK, Gonzalez C, Hodge A, Jacobs Jr DR, Joseph JJ, Khalili D, Magliano DJ, Mehlig K, Milne R, Mishra G, Mongraw-Chaffin M, Pasco JA, Sakurai M, Schreiner PJ, Selvin E, Shaw JE, Wittert G, Yatsuya H, Huxley RR. Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes. BMJ Open Diabetes Res Care 2019; 7:e000794. [PMID: 31908797 PMCID: PMC6936411 DOI: 10.1136/bmjdrc-2019-000794] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 10/16/2019] [Accepted: 11/22/2019] [Indexed: 01/05/2023] Open
Abstract
Objective There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful. Research design and methods We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points. Results Sixteen studies, with 76 513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1 mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6 mmol/L, 2-hour postload glucose 7.0 mmol/L and HbA1c 5.6% (38 mmol/mol). Conclusions In terms of identifying individuals at greatest risk of developing diabetes within 5 years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.
Collapse
Affiliation(s)
- Crystal Man Ying Lee
- School of Psychology and Public Health, La Trobe University, Bundoora, Victoria, Australia
- Boden Collaboration for Obesity, Nutrition and Exercise & Eating Disorders, University of Sydney, Sydney, New South Wales, Australia
| | - Stephen Colagiuri
- Boden Collaboration for Obesity, Nutrition and Exercise & Eating Disorders, University of Sydney, Sydney, New South Wales, Australia
| | - Mark Woodward
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- The George Institute for Global Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Edward W Gregg
- Department of Epidemiology and Statistics, School of Public Health, Imperial College London, London, UK
| | - Robert Adams
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
- Respiratory and Sleep Service, Southern Adelaide Local Health Network, SA Health, Adelaide, South Australia, Australia
- Faculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Rafael Gabriel
- National School of Public Health, National Institute of Health Carlos III, Madrid, Spain
| | - Tiffany K Gill
- Faculty of Health and Medical Sciences, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| | - Clicerio Gonzalez
- Unidad de Investigación en Diabetes y Riesgo Cardiovascular, Instituto Nacional de Salud Publica, Cuernavaca, Morelos, Mexico
| | - Allison Hodge
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - David R Jacobs Jr
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Joshua J Joseph
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Biostatistics and Epidemiology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Dianna J Magliano
- Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Kirsten Mehlig
- Department of Public Health and Community Medicine, Institute of Medicine, University of Gothenburg, Goteborg, Sweden
| | - Roger Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Gita Mishra
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Queensland, Australia
| | - Morgana Mongraw-Chaffin
- Department of Epidemiology & Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Julie A Pasco
- Department of Clinical and Biomedical Sciences, Barwon Health, The University of Melbourne, Geelong, Victoria, Australia
- School of Medicine, Faculty of Health, Deakin University, Geelong, Victoria, Australia
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Masaru Sakurai
- Department of Social and Environmental Medicine, Kanazawa Medical University, Uchinada, Ishikawa, Japan
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jonathan E Shaw
- Clinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Gary Wittert
- Discipline of Medicine, Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia
| | - Hiroshi Yatsuya
- Department of Public Health, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan
- Department of Public Health and Health Systems, Nagoya University Graduate School of Medicine, Nagoya, Aichi, Japan
| | - Rachel R Huxley
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
- College of Science, Health and Engineering, La Trobe University, Bundoora, Victoria, Australia
| |
Collapse
|
30
|
Williamson EJ, Polak J, Simpson JA, Giles GG, English DR, Hodge A, Gurrin L, Forbes AB. Sustained adherence to a Mediterranean diet and physical activity on all-cause mortality in the Melbourne Collaborative Cohort Study: application of the g-formula. BMC Public Health 2019; 19:1733. [PMID: 31878916 PMCID: PMC6933918 DOI: 10.1186/s12889-019-7919-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 11/08/2019] [Indexed: 12/27/2022] Open
Abstract
Background Adherence to a traditional Mediterranean diet has been associated with lower mortality and cardiovascular disease risk. The relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time remains unknown. Methods We used the parametric G-formula to account for time-dependent confounding, in order to assess the relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time. We included healthy Melbourne Collaborative Cohort Study participants attending a visit during 1995–1999. Questionnaires assessed diet and physical activity at each of three study waves. Deaths were identified by linkage to national registries. We estimated mortality risk over approximately 14 years (1995–2011). Results Of 22,213 participants, 2163 (9.7%) died during 13.6 years median follow-up. Sustained high physical activity and adherence to a Mediterranean-style diet resulted in an estimated reduction in all-cause mortality of 1.82 per 100 people (95% confidence interval (CI): 0.03, 3.6). The population attributable fraction was 13% (95% CI: 4, 23%) for sustained high physical activity, 7% (95% CI: − 3, 17%) for sustained adherence to a Mediterranean-style diet and 18% (95% CI: 0, 36%) for their combination. Conclusions A small reduction in mortality may be achieved by sustained elevated physical activity levels in healthy middle-aged adults, but there may be comparatively little gain from increasing adherence to a Mediterranean-style diet.
Collapse
Affiliation(s)
- Elizabeth J Williamson
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK. .,, Health Data Research UK (HDR UK), UK.
| | - Julia Polak
- The Victorian Centre for Biostatistics (ViCBiostat), Melbourne, Victoria, Australia
| | - Julie A Simpson
- The Victorian Centre for Biostatistics (ViCBiostat), Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Dallas R English
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Allison Hodge
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.,Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Lyle Gurrin
- The Victorian Centre for Biostatistics (ViCBiostat), Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Andrew B Forbes
- The Victorian Centre for Biostatistics (ViCBiostat), Melbourne, Victoria, Australia.,Department of Epidemiology & Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| |
Collapse
|
31
|
D'Arcy E, Rayner J, Hodge A, Ross LJ, Schoenaker DAJM. The Role of Diet in the Prevention of Diabetes among Women with Prior Gestational Diabetes: A Systematic Review of Intervention and Observational Studies. J Acad Nutr Diet 2019; 120:69-85.e7. [PMID: 31636052 DOI: 10.1016/j.jand.2019.07.021] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Accepted: 07/26/2019] [Indexed: 01/23/2023]
Abstract
BACKGROUND Women with prior gestational diabetes (GDM) have an increased lifetime risk of developing type 2 diabetes mellitus (T2DM). There are no up-to-date systematic reviews analyzing the relationship of diet with risk of developing T2DM following GDM. OBJECTIVE To systematically review the evidence from intervention and observational studies on effects of dietary interventions and associations of dietary intake with T2DM outcomes in women with a GDM history. METHODS Six electronic databases were searched (Cumulative Index to Nursing and Allied Health Literature, Embase, Medline, Cochrane Central, Proquest, and Scopus) for articles published until May 2019. This review includes intervention and observational studies among women of any age with a history of GDM that reported on the effects of dietary interventions or association of dietary intake (energy, nutrients, foods, dietary patterns) with T2DM, impaired glucose tolerance, impaired fasting glucose, or prediabetes. RESULTS The systematic review identified five articles reporting results from four intervention studies, and seven articles reporting results from four observational studies. Findings from intervention studies indicated trends toward beneficial effects of a low-glycemic index diet, a low-carbohydrate diet, and a diet in line with general population dietary guidelines, but studies had unclear or high risk of bias. Findings from two cross-sectional and one prospective study indicated poorer diabetes outcomes for women with higher intakes of branched-chain amino acids, total and heme iron, and a diet relatively low in carbohydrates and high in animal fat and protein, and better outcomes among those consuming diets rich in fruit, vegetables, nuts, fish, and legumes, and low in red and processed meats and sugar-sweetened beverages, after adjustment for confounders, including body mass index. CONCLUSIONS Findings from observational studies support current dietary guidelines for the prevention of T2DM. Further dietary intervention studies are needed to confirm whether or not dietary modification following a GDM pregnancy reduces women's risk of developing T2DM.
Collapse
|
32
|
Taylor LF, Hodge A. Impact of a single treatment of injectable doramectin on weight gain post weaning in beef heifers and steers in central Queensland, Australia. Aust Vet J 2019; 97:185-190. [PMID: 31136696 DOI: 10.1111/avj.12809] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 03/04/2019] [Accepted: 03/20/2019] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To demonstrate the impact of a single drench with a label dose of injectable doramectin subsequent to weaning on the growth and performance of heifers and steers in central Queensland beef herds. METHODS Three studies were undertaken on recently-weaned Bos indicus-cross beef calves with ≥ 75% B. indicus content on two farms in central Queensland, just north of the Tropic of Capricorn. Farm 1 was located 50 km north and Farm 2 75 km north-west of Rockhampton. In each study, half of a group of recently-weaned beef calves were treated by random allocation with 0.2 mg/kg of injectable doramectin, and the remainder acting as untreated controls. Study 1 (Farm 1) enrolled 250 heifers, while studies 2 and 3 (Farm 2) both enrolled 200 steers and 200 heifers. The farms involved did not historically use macrocyclic lactone-based drenches on their cattle. There were varying periods of follow-up, with treated and control cattle pastured as one group throughout the study period. Worm burdens were monitored using standard faecal egg counts and larval differentiation procedures. In all studies, the worm genera present were a mix of Cooperia spp., Haemonchus spp. and Oesophagostomum spp. RESULTS In study 1, conducted on Farm 1 beginning 9 July 2012, doramectin-treated cattle gained an average of 0.27 kg/day while control cattle gained 0.19 kg/day over a monitoring period of 121 days (P < 0.0001). In study 2, conducted on Farm 2 beginning 28 July 2015, doramectin-treated cattle gained an average of 0.15 kg/day versus 0.145 kg/day in the control group (P = 0.44) over a 231-day study period. In study 3, conducted on Farm 2 beginning 4 August 2016, doramectin-treated steers and heifers gained an average of 0.431 and 0.402 kg/day versus 0.342 and 0.311 kg/day in the control group, respectively, over the first 91 days of the study (P < 0.0001 in both cases). The differences in average daily gain (ADG) in subsequent time periods were not statistically significant for steers or heifers. However, overall differences in ADG from day 0 remained statistically significant out to day 258, when the study ended for the heifers. By day 594, when the study ended for the steers, the difference in ADG was no longer significant. CONCLUSION Treatment with injectable doramectin soon after weaning resulted in improved weight gain in the 3 months after weaning in two of the three studies.
Collapse
Affiliation(s)
- L F Taylor
- Zoetis Australia, Level 6, 5 Rider Boulevard, Rhodes, New South Wales, 2138, Australia
| | - A Hodge
- Zoetis Australia, Level 6, 5 Rider Boulevard, Rhodes, New South Wales, 2138, Australia
| |
Collapse
|
33
|
Marklund M, Wu JHY, Imamura F, Del Gobbo LC, Fretts A, de Goede J, Shi P, Tintle N, Wennberg M, Aslibekyan S, Chen TA, de Oliveira Otto MC, Hirakawa Y, Eriksen HH, Kröger J, Laguzzi F, Lankinen M, Murphy RA, Prem K, Samieri C, Virtanen J, Wood AC, Wong K, Yang WS, Zhou X, Baylin A, Boer JM, Brouwer IA, Campos H, Chaves PHM, Chien KL, de Faire U, Djoussé L, Eiriksdottir G, El-Abbadi N, Forouhi NG, Gaziano JM, Geleijnse JM, Gigante B, Giles G, Guallar E, Gudnason V, Harris T, Harris WS, Helmer C, Hellenius ML, Hodge A, Hu FB, Jacques PF, Jansson JH, Kalsbeek A, Khaw KT, Koh WP, Laakso M, Leander K, Hung-Ju Lin, Lind L, Luben R, Luo J, McKnight B, Mursu J, Ninomiya T, Overvad K, Psaty BM, Rimm E, Schulze MB, Siscovick D, Nielsen MS, Smith AV, Steffen BT, Steffen L, Sun Q, Sundström J, Tsai MY, Tunstall-Pedoe H, Uusitupa MIJ, van Dam RM, Veenstra J, Verschuren WM, Wareham N, Willett W, Woodward M, Yuan JM, Micha R, Lemaitre RN, Mozaffarian D. Biomarkers of Dietary Omega-6 Fatty Acids and Incident Cardiovascular Disease and Mortality. Circulation 2019; 139:2422-2436. [PMID: 30971107 PMCID: PMC6582360 DOI: 10.1161/circulationaha.118.038908] [Citation(s) in RCA: 174] [Impact Index Per Article: 34.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
BACKGROUND Global dietary recommendations for and cardiovascular effects of linoleic acid, the major dietary omega-6 fatty acid, and its major metabolite, arachidonic acid, remain controversial. To address this uncertainty and inform international recommendations, we evaluated how in vivo circulating and tissue levels of linoleic acid (LA) and arachidonic acid (AA) relate to incident cardiovascular disease (CVD) across multiple international studies. METHODS We performed harmonized, de novo, individual-level analyses in a global consortium of 30 prospective observational studies from 13 countries. Multivariable-adjusted associations of circulating and adipose tissue LA and AA biomarkers with incident total CVD and subtypes (coronary heart disease, ischemic stroke, cardiovascular mortality) were investigated according to a prespecified analytic plan. Levels of LA and AA, measured as the percentage of total fatty acids, were evaluated linearly according to their interquintile range (ie, the range between the midpoint of the first and fifth quintiles), and categorically by quintiles. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Heterogeneity was explored by age, sex, race, diabetes mellitus, statin use, aspirin use, omega-3 levels, and fatty acid desaturase 1 genotype (when available). RESULTS In 30 prospective studies with medians of follow-up ranging 2.5 to 31.9 years, 15 198 incident cardiovascular events occurred among 68 659 participants. Higher levels of LA were significantly associated with lower risks of total CVD, cardiovascular mortality, and ischemic stroke, with hazard ratios per interquintile range of 0.93 (95% CI, 0.88-0.99), 0.78 (0.70-0.85), and 0.88 (0.79-0.98), respectively, and nonsignificantly with lower coronary heart disease risk (0.94; 0.88-1.00). Relationships were similar for LA evaluated across quintiles. AA levels were not associated with higher risk of cardiovascular outcomes; in a comparison of extreme quintiles, higher levels were associated with lower risk of total CVD (0.92; 0.86-0.99). No consistent heterogeneity by population subgroups was identified in the observed relationships. CONCLUSIONS In pooled global analyses, higher in vivo circulating and tissue levels of LA and possibly AA were associated with lower risk of major cardiovascular events. These results support a favorable role for LA in CVD prevention.
Collapse
Affiliation(s)
- Matti Marklund
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Sweden
- The George Institute for Global Health and the Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Jason HY Wu
- The George Institute for Global Health and the Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom
| | - Liana C. Del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA
| | - Amanda Fretts
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Janette de Goede
- Division of Human Nutrition, Wageningen University, The Netherlands
| | - Peilin Shi
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt College, Sioux Centre, IA
| | - Maria Wennberg
- Department of Public Health and Clinical Medicine, Nutritional Research, Umeå University, Sweden
| | | | - Tzu-An Chen
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX
| | - Marcia C. de Oliveira Otto
- Division of Epidemiology, Human Genetics and Environmental Sciences, the University of Texas Health Science Center, School of Public Health, Houston
| | - Yoichiro Hirakawa
- Department of Medicine and Clinical Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Janine Kröger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Federica Laguzzi
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio
| | - Rachel A. Murphy
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Kiesha Prem
- Saw Swee Hock School of Public Health, National University of Singapore
| | - Cécilia Samieri
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, TUMR 1219, France
| | - Jyrki Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio
| | - Alexis C. Wood
- USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX
| | - Kerry Wong
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Australia
| | - Wei-Sin Yang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei
| | - Xia Zhou
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Ana Baylin
- Departments of Nutritional Sciences and Epidemiology, School of Public Health, University of Michigan, Ann Arbor
| | - Jolanda M.A. Boer
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
| | | | - Hannia Campos
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Paulo H. M. Chaves
- Benjamin Leon for Geriatrics Research and Education, Herbert Wertheim College of Medicine, Florida International University, Miami
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei
- Department of Internal Medicine, National Taiwan University Hospital, Taipei
| | - Ulf de Faire
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Luc Djoussé
- Brigham and Women's Hospital, Boston Veterans Affairs Healthcare System, MA
| | - Gudny Eiriksdottir
- Icelandic Heart Association, Kópavogur, Iceland; and Faculty of Medicine, University of Iceland, Reykjavik
| | - Naglaa El-Abbadi
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
- USDA Jean Mayer Human Nutrition Research Center, Boston, MA
| | - Nita G. Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom
| | - J. Michael Gaziano
- Brigham and Women's Hospital, Boston Veterans Affairs Healthcare System, MA
| | | | - Bruna Gigante
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Graham Giles
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Australia
| | - Eliseo Guallar
- Division of Environmental Epidemiology, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kópavogur, Iceland; and Faculty of Medicine, University of Iceland, Reykjavik
| | | | - William S. Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls
- OmegaQuant Analytics, LLC, Sioux Falls, SD
| | - Catherine Helmer
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, TUMR 1219, France
| | - Mai-Lis Hellenius
- Department of Medicine, Cardiology Unit, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Allison Hodge
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Australia
| | - Frank B. Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Paul F. Jacques
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
- USDA Jean Mayer Human Nutrition Research Center, Boston, MA
| | - Jan-Håkan Jansson
- Department of Public Health and Clinical Medicine, Research Unit Skellefteå, Umeå University, Umeå, Sweden
| | - Anya Kalsbeek
- Department of Mathematics and Statistics, Dordt College, Sioux Centre, IA
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, United Kingdom
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore
- Duke-NUS Medical School, Singapore
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Karin Leander
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Sweden
| | - Robert Luben
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, United Kingdom
| | - Juhua Luo
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington
| | - Barbara McKnight
- Department of Biostatistics, School of Public Health, University of Washington, Seattle
| | - Jaakko Mursu
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, Denmark
- Department of Cardiology, Aalborg University Hospital, Denmark
| | - Bruce M. Psaty
- Cardiovascular Health Study, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Eric Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | | | | | - Albert V. Smith
- Icelandic Heart Association, Kópavogur, Iceland; and Faculty of Medicine, University of Iceland, Reykjavik
| | - Brian T. Steffen
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Lyn Steffen
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | | | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Hugh Tunstall-Pedoe
- Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, United Kingdom
| | - Matti I. J. Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore
| | - Jenna Veenstra
- Department of Mathematics and Statistics, Dordt College, Sioux Centre, IA
| | - W.M. Monique Verschuren
- Centre for Nutrition, Prevention and Health Services, National Institute of Public Health and the Environment, Bilthoven, The Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Nick Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, United Kingdom
| | - Walter Willett
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Mark Woodward
- The George Institute for Global Health and the Faculty of Medicine, University of New South Wales, Sydney, Australia
- Cardiovascular Epidemiology Unit, Institute of Cardiovascular Research, University of Dundee, United Kingdom
- The George Institute for Global Health, University of Oxford, United Kingdom
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer, and Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, PA
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA
| | | |
Collapse
|
34
|
McCrory C, Leahy S, Ribeiro AI, Fraga S, Barros H, Avendano M, Vineis P, Layte R, Baglietto L, Bartley M, Bellone M, Berger E, Bochud M, Candiani G, Carmeli C, Carra L, Castagne R, Chadeau‐Hyam M, Cima S, Costa G, Courtin E, Delpierre C, D'Errico A, Donkin A, Dugué P, Elliott P, Fagherazzi G, Fiorito G, Gandini M, Gares V, Gerbouin‐Rerrolle P, Giles G, Goldberg M, Greco D, Guida F, Hodge A, Karimi M, Karisola P, Kelly M, Kivimaki M, Laine J, Lang T, Laurent A, Lepage B, Lorsch D, Machell G, Mackenbach J, Marmot M, Milne R, Muennig P, Nusselder W, Petrovic D, Polidoro S, Preisig M, Recalcati P, Reinhard E, Ricceri F, Robinson O, Jose Rubio Valverde, Severi G, Simmons T, Stringhini S, Terhi V, Than J, Vergnaud A, Vigna‐Taglianti F, Vollenweider P, Zins M. Maternal educational inequalities in measured body mass index trajectories in three European countries. Paediatr Perinat Epidemiol 2019; 33:226-237. [PMID: 31090081 DOI: 10.1111/ppe.12552] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 03/05/2019] [Accepted: 03/16/2019] [Indexed: 12/17/2022]
Abstract
BACKGROUND Social inequalities in the prevalence of childhood overweight and obesity are well-established, but less is known about when the social gradient first emerges and how it evolves across childhood and adolescence. OBJECTIVE This study examines maternal education differentials in children's body mass trajectories in infancy, childhood and adolescence using data from four contemporary European child cohorts. METHODS Prospective data on children's body mass index (BMI) were obtained from four cohort studies-Generation XXI (G21-Portugal), Growing Up in Ireland (GUI) infant and child cohorts, and the Millennium Cohort Study (MCS-UK)-involving a total sample of 41,399 children and 120,140 observations. Children's BMI trajectories were modelled by maternal education level using mixed-effect models. RESULTS Maternal educational inequalities in children's BMI were evident as early as three years of age. Children from lower maternal educational backgrounds were characterised by accelerated BMI growth, and the extent of the disparity was such that boys from primary-educated backgrounds measured 0.42 kg/m2 (95% CI 0.24, 0.60) heavier at 7 years of age in G21, 0.90 kg/m2 (95% CI 0.60, 1.19) heavier at 13 years of age in GUI and 0.75 kg/m2 (95% CI 0.52, 0.97) heavier in MCS at 14 years of age. The corresponding figures for girls were 0.71 kg/m2 (95% CI 0.50, 0.91), 1.31 kg/m2 (95% CI 1.00, 1.62) and 0.76 kg/m2 (95% CI 0.53, 1.00) in G21, GUI and MCS, respectively. CONCLUSIONS Maternal education is a strong predictor of BMI across European nations. Socio-economic differentials emerge early and widen across childhood, highlighting the need for early intervention.
Collapse
Affiliation(s)
- Cathal McCrory
- Department of Medical Gerontology, The Irish Longitudinal Study on Ageing (TILDA), Trinity College Dublin, Dublin, Ireland
| | - Siobhan Leahy
- Faculty of Education and Health Sciences, Health Research Institute, University of Limerick, Limerick, Ireland
| | - Ana Isabel Ribeiro
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | - Silvia Fraga
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | - Henrique Barros
- EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | - Mauricio Avendano
- Department of Social Science, Health and Medicine, Kings College London, London, UK
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Richard Layte
- Department of Sociology, Trinity College Dublin, Dublin, Ireland
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
35
|
Hill E, Hodge A, Clifton P, Shivappa N, Hebert JR, Dennerstein L, Campbell S, Szoeke C. Longitudinal nutritional changes in aging Australian women. Asia Pac J Clin Nutr 2019; 28:139-149. [PMID: 30896425 DOI: 10.6133/apjcn.201903_28(1).0019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
BACKGROUND AND OBJECTIVES The importance of diet for the maintenance of health during aging is attracting a growing body of research interest. Given dietary intakes, along with BMI, are substantial contributors to disease burden, this study aimed to investigate prospective changes in dietary patterns and nutrient intakes in a sample of mid to late-life women over 14 years. METHODS AND STUDY DESIGN Participants were from the Women's Healthy Ageing Project (WHAP); a longitudinal cohort of Australian-born women within the Melbourne metropolitan area. 173 participants were included in this analysis, their mean age in 1998 was 55 years (range 51-62) and in 2012 was 70 years (range 66-76). Diet was assessed using the Dietary Questionnaire for Epidemiological Studies Version 2 in 1998 and 2012. Nutritional intakes, Dietary Inflammatory Index (DII®) scores, Mediterranean Diet (MD) scores, sociodemographic and physical measures were calculated for all participants at both time points. RESULTS Energy intake was found to significantly decrease over time (p<0.005). Energy-adjusted (i.e., energy density) total fat, saturated fat, monounsaturated fat and cholesterol intakes increased over time (all p<0.002), while energy-adjusted and absolute carbohydrate intake decreased (p<0.002). Adherence to the MD decreased over time (p<0.001) whilst DII scores increased slightly over time, although this result was not significant. CONCLUSIONS This study shows significant changes in the intake of energy and several nutrients in a cohort of aging Australian women in the Melbourne metropolitan area over a period of 14 years. Between 1998 and 2012, changes in indices reflecting overall diet were consistently in the direction of a poorer diet.
Collapse
Affiliation(s)
- Edward Hill
- Centre for Medical Research, Department of Medicine-Royal Melbourne Hospital, University of Melbourne,Victoria, Australia.,Institute for Health & Ageing, Melbourne, Victoria, Australia
| | - Allison Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council of Victoria, Melbourne, Victoria, Australia.,Centre for Epidemiology and Biostatistics, University of Melbourne, Australia
| | - Peter Clifton
- School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Nitin Shivappa
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, USA.,Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.,Connecting Health Innovations LLC, Columbia, USA
| | - James R Hebert
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, USA.,Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, USA.,Connecting Health Innovations LLC, Columbia, USA
| | | | | | - Cassandra Szoeke
- Centre for Medical Research, Department of Medicine-Royal Melbourne Hospital, University of Melbourne,Victoria, Australia. .,Institute for Health & Ageing, Melbourne, Victoria, Australia
| |
Collapse
|
36
|
Zuo H, Ueland PM, Midttun Ø, Tell GS, Fanidi A, Zheng W, Shu X, Xiang Y, Wu J, Prentice R, Pettinger M, Thomson CA, Giles GG, Hodge A, Cai Q, Blot WJ, Johansson M, Hultdin J, Grankvist K, Stevens VL, McCullough ML, Weinstein SJ, Albanes D, Ziegler RG, Freedman ND, Caporaso NE, Langhammer A, Hveem K, Næss M, Buring JE, Lee I, Gaziano JM, Severi G, Zhang X, Stampfer MJ, Han J, Zeleniuch-Jacquotte A, Marchand LL, Yuan J, Wang R, Koh W, Gao Y, Ericson U, Visvanathan K, Jones MR, Relton C, Brennan P, Johansson M, Ulvik A. Vitamin B6 catabolism and lung cancer risk: results from the Lung Cancer Cohort Consortium (LC3). Ann Oncol 2019; 30:478-485. [PMID: 30698666 PMCID: PMC6442648 DOI: 10.1093/annonc/mdz002] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Increased vitamin B6 catabolism related to inflammation, as measured by the PAr index (the ratio of 4-pyridoxic acid over the sum of pyridoxal and pyridoxal-5'-phosphate), has been positively associated with lung cancer risk in two prospective European studies. However, the extent to which this association translates to more diverse populations is not known. MATERIALS AND METHODS For this study, we included 5323 incident lung cancer cases and 5323 controls individually matched by age, sex, and smoking status within each of 20 prospective cohorts from the Lung Cancer Cohort Consortium. Cohort-specific odds ratios (ORs) and 95% confidence intervals (CIs) for the association between PAr and lung cancer risk were calculated using conditional logistic regression and pooled using random-effects models. RESULTS PAr was positively associated with lung cancer risk in a dose-response fashion. Comparing the fourth versus first quartiles of PAr resulted in an OR of 1.38 (95% CI: 1.19-1.59) for overall lung cancer risk. The association between PAr and lung cancer risk was most prominent in former smokers (OR: 1.69, 95% CI: 1.36-2.10), men (OR: 1.60, 95% CI: 1.28-2.00), and for cancers diagnosed within 3 years of blood draw (OR: 1.73, 95% CI: 1.34-2.23). CONCLUSION Based on pre-diagnostic data from 20 cohorts across 4 continents, this study confirms that increased vitamin B6 catabolism related to inflammation and immune activation is associated with a higher risk of developing lung cancer. Moreover, PAr may be a pre-diagnostic marker of lung cancer rather than a causal factor.
Collapse
Affiliation(s)
- H Zuo
- Department of Global Public Health and Primary Care, University of Bergen, Bergen.
| | - P M Ueland
- Department of Clinical Science, University of Bergen, Bergen; Laboratory of Medicine and Pathology, Haukeland University Hospital, Bergen
| | | | - G S Tell
- Department of Global Public Health and Primary Care, University of Bergen, Bergen
| | - A Fanidi
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - W Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - X Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - Y Xiang
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - J Wu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - R Prentice
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle
| | - M Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle
| | - C A Thomson
- Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, USA
| | - G G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - A Hodge
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Q Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - W J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - M Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Umeå
| | - J Hultdin
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - K Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - V L Stevens
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta
| | - M L McCullough
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta
| | - S J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - D Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - R G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - N D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - N E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, USA
| | - A Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - K Hveem
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - M Næss
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - J E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston
| | - I Lee
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston
| | - J M Gaziano
- Division of Aging, Brigham and Women's Hospital, Boston; VA Boston Healthcare System, Boston, USA
| | - G Severi
- Human Genetics Foundation (HuGeF), Torin, Italy; CESP (U1018 INSERM), Université Paris-Saclay, USQ, Villejuif, France
| | - X Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston
| | - M J Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston
| | - J Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Melvin & Bren Simon Cancer Center, Indiana University, Indianapolis
| | | | - L L Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu
| | - J Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
| | - R Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh
| | - W Koh
- Duke-NUS Medical School, Singapore and Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Y Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiaotong University, Shanghai, China
| | - U Ericson
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - K Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, Baltimore, USA
| | - M R Jones
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, Baltimore, USA
| | - C Relton
- Institute of Genetic Medicine, Newcastle University, Newcastle; MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
| | - P Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - M Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | | |
Collapse
|
37
|
Muller DC, Larose TL, Hodge A, Guida F, Langhammer A, Grankvist K, Meyer K, Cai Q, Arslan AA, Zeleniuch-Jacquotte A, Albanes D, Giles GG, Sesso HD, Lee IM, Gaziano JM, Yuan JM, Hoffman Bolton J, Buring JE, Visvanathan K, Le Marchand L, Purdue MP, Caporaso NE, Midttun Ø, Ueland PM, Prentice RL, Weinstein SJ, Stevens VL, Zheng W, Blot WJ, Shu XO, Zhang X, Xiang YB, Koh WP, Hveem K, Thomson CA, Pettinger M, Engström G, Brunnström H, Milne RL, Stampfer MJ, Han J, Johansson M, Brennan P, Severi G, Johansson M. Circulating high sensitivity C reactive protein concentrations and risk of lung cancer: nested case-control study within Lung Cancer Cohort Consortium. BMJ 2019; 364:k4981. [PMID: 30606716 PMCID: PMC6315896 DOI: 10.1136/bmj.k4981] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/01/2018] [Indexed: 12/21/2022]
Abstract
OBJECTIVES To conduct a comprehensive analysis of prospectively measured circulating high sensitivity C reactive protein (hsCRP) concentration and risk of lung cancer overall, by smoking status (never, former, and current smokers), and histological sub-type. DESIGN Nested case-control study. SETTING 20 population based cohort studies in Asia, Europe, Australia, and the United States. PARTICIPANTS 5299 patients with incident lung cancer, with individually incidence density matched controls. EXPOSURE Circulating hsCRP concentrations in prediagnostic serum or plasma samples. MAIN OUTCOME MEASURE Incident lung cancer diagnosis. RESULTS A positive association between circulating hsCRP concentration and the risk of lung cancer for current (odds ratio associated with a doubling in hsCRP concentration 1.09, 95% confidence interval 1.05 to 1.13) and former smokers (1.09, 1.04 to 1.14) was observed, but not for never smokers (P<0.01 for interaction). This association was strong and consistent across all histological subtypes, except for adenocarcinoma, which was not strongly associated with hsCRP concentration regardless of smoking status (odds ratio for adenocarcinoma overall 0.97, 95% confidence interval 0.94 to 1.01). The association between circulating hsCRP concentration and the risk of lung cancer was strongest in the first two years of follow-up for former and current smokers. Including hsCRP concentration in a risk model, in addition to smoking based variables, did not improve risk discrimination overall, but slightly improved discrimination for cancers diagnosed in the first two years of follow-up. CONCLUSIONS Former and current smokers with higher circulating hsCRP concentrations had a higher risk of lung cancer overall. Circulating hsCRP concentration was not associated with the risk of lung adenocarcinoma. Circulating hsCRP concentration could be a prediagnostic marker of lung cancer rather than a causal risk factor.
Collapse
Affiliation(s)
- David C Muller
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- Department of Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London W2 1PG, UK
| | - Tricia L Larose
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Allison Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Florence Guida
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alan A Arslan
- Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY, USA
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, USA
| | - Anne Zeleniuch-Jacquotte
- Department of Population Health and Environmental Medicine, New York University School of Medicine, New York, NY, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Graham G Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Howard D Sesso
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - I-Min Lee
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - J Michael Gaziano
- Division of Aging, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Boston VA Medical Center, Boston, MA, USA
| | - Jian-Min Yuan
- UPMC Hillman Cancer Center, University of Pittsburgh, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, USA
| | - Judith Hoffman Bolton
- George W Comstock Center for Public Health Research and Prevention Health Monitoring Unit, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Julie E Buring
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Kala Visvanathan
- George W Comstock Center for Public Health Research and Prevention Health Monitoring Unit, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Loic Le Marchand
- Epidemiology Program, Cancer Research Center of Hawaii, University of Hawaii, Honolulu, HI, USA
| | - Mark P Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | | | - Per M Ueland
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
| | - Ross L Prentice
- Division of Public Health Sciences Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Victoria L Stevens
- Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Yong-Bing Xiang
- State Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | | | - Kristian Hveem
- KG Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Cynthia A Thomson
- Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Mary Pettinger
- Division of Public Health Sciences Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Gunnar Engström
- Department of Clinical Science in Malmö, Lund University, Malmö, Sweden
| | - Hans Brunnström
- Pathology, Department of Clinical Sciences Lund, Laboratory Medicine Region Skåne, Lund University, Lund, Sweden
| | - Roger L Milne
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC, Australia
| | - Meir J Stampfer
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Jiali Han
- Department of Epidemiology, Richard M Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
- Melvin and Bren Simon Cancer Center, Indiana University, Indianapolis, IN, USA
| | | | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Gianluca Severi
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Italian Institute for Genomic Medicine (IIGM), Torino, Italy
- Centre de Recherche en Epidemiologie et Santé des Populations (CESP) UMR1018 Inserm, Facultés de Médicine Université Paris-Saclay, UPS, UVSQ, Villejuif, France
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| |
Collapse
|
38
|
Jacka FN, O'Neil A, Itsiopoulos C, Opie R, Cotton S, Mohebbi M, Castle D, Dash S, Mihalopoulos C, Chatterton ML, Brazionis L, Dean OM, Hodge A, Berk M. The SMILES trial: an important first step. BMC Med 2018; 16:237. [PMID: 30591059 PMCID: PMC6309069 DOI: 10.1186/s12916-018-1228-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 11/30/2018] [Indexed: 11/10/2022] Open
Abstract
The SMILES trial was the first intervention study to test dietary improvement as a treatment strategy for depression. Molendijk et al. propose that expectation bias and difficulties with blinding might account for the large effect size. While we acknowledge the issue of expectation bias in lifestyle intervention trials and indeed discuss this as a key limitation in our paper, we observed a strong correlation between dietary change and change in depression scores, which we argue is consistent with a causal effect and we believe unlikely to be an artefact of inadequate blinding. Since its publication, our results have been largely replicated and our recent economic evaluation of SMILES suggests that the benefits of our approach extend beyond depression. We argue that the SMILES trial should be considered an important, albeit preliminary, first step in the field of nutritional psychiatry research.
Collapse
Affiliation(s)
- Felice N Jacka
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia.
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, VIC, Australia.
- Black Dog Institute, Randwick, NSW, Australia.
| | - Adrienne O'Neil
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia
- School of Population Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Catherine Itsiopoulos
- Department of Rehabilitation, Nutrition and Sport, La Trobe University, Melbourne, VIC, Australia
| | - Rachelle Opie
- Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia
| | - Sue Cotton
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Mohammadreza Mohebbi
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia
- Biostatistics Unit, Faculty of Health, Deakin University, Geelong, VIC, Australia
| | - David Castle
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- St Vincent's Hospital, Melbourne, VIC, Australia
| | - Sarah Dash
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia
| | | | - Mary Lou Chatterton
- Centre for Population Health Research, Deakin University, Geelong, VIC, Australia
| | - Laima Brazionis
- Department of Rehabilitation, Nutrition and Sport, La Trobe University, Melbourne, VIC, Australia
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
| | - Olivia M Dean
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Allison Hodge
- Cancer Intelligence and Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Michael Berk
- IMPACT Strategic Research Centre, Deakin University, Geelong, VIC, Australia
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| |
Collapse
|
39
|
Imamura F, Fretts A, Marklund M, Ardisson Korat AV, Yang WS, Lankinen M, Qureshi W, Helmer C, Chen TA, Wong K, Bassett JK, Murphy R, Tintle N, Yu CI, Brouwer IA, Chien KL, Frazier-Wood AC, del Gobbo LC, Djoussé L, Geleijnse JM, Giles GG, de Goede J, Gudnason V, Harris WS, Hodge A, Hu F, Koulman A, Laakso M, Lind L, Lin HJ, McKnight B, Rajaobelina K, Risérus U, Robinson JG, Samieri C, Siscovick DS, Soedamah-Muthu SS, Sotoodehnia N, Sun Q, Tsai MY, Uusitupa M, Wagenknecht LE, Wareham NJ, Wu JHY, Micha R, Forouhi NG, Lemaitre RN, Mozaffarian D. Fatty acid biomarkers of dairy fat consumption and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies. PLoS Med 2018; 15:e1002670. [PMID: 30303968 PMCID: PMC6179183 DOI: 10.1371/journal.pmed.1002670] [Citation(s) in RCA: 129] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 09/07/2018] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND We aimed to investigate prospective associations of circulating or adipose tissue odd-chain fatty acids 15:0 and 17:0 and trans-palmitoleic acid, t16:1n-7, as potential biomarkers of dairy fat intake, with incident type 2 diabetes (T2D). METHODS AND FINDINGS Sixteen prospective cohorts from 12 countries (7 from the United States, 7 from Europe, 1 from Australia, 1 from Taiwan) performed new harmonised individual-level analysis for the prospective associations according to a standardised plan. In total, 63,682 participants with a broad range of baseline ages and BMIs and 15,180 incident cases of T2D over the average of 9 years of follow-up were evaluated. Study-specific results were pooled using inverse-variance-weighted meta-analysis. Prespecified interactions by age, sex, BMI, and race/ethnicity were explored in each cohort and were meta-analysed. Potential heterogeneity by cohort-specific characteristics (regions, lipid compartments used for fatty acid assays) was assessed with metaregression. After adjustment for potential confounders, including measures of adiposity (BMI, waist circumference) and lipogenesis (levels of palmitate, triglycerides), higher levels of 15:0, 17:0, and t16:1n-7 were associated with lower incidence of T2D. In the most adjusted model, the hazard ratio (95% CI) for incident T2D per cohort-specific 10th to 90th percentile range of 15:0 was 0.80 (0.73-0.87); of 17:0, 0.65 (0.59-0.72); of t16:1n7, 0.82 (0.70-0.96); and of their sum, 0.71 (0.63-0.79). In exploratory analyses, similar associations for 15:0, 17:0, and the sum of all three fatty acids were present in both genders but stronger in women than in men (pinteraction < 0.001). Whereas studying associations with biomarkers has several advantages, as limitations, the biomarkers do not distinguish between different food sources of dairy fat (e.g., cheese, yogurt, milk), and residual confounding by unmeasured or imprecisely measured confounders may exist. CONCLUSIONS In a large meta-analysis that pooled the findings from 16 prospective cohort studies, higher levels of 15:0, 17:0, and t16:1n-7 were associated with a lower risk of T2D.
Collapse
Affiliation(s)
- Fumiaki Imamura
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Amanda Fretts
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Matti Marklund
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Sweden
| | - Andres V. Ardisson Korat
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Wei-Sin Yang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Taiwan
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Waqas Qureshi
- Section of Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Bowman Gray Center, Winston-Salem, North Carolina, United States of America
| | - Catherine Helmer
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Tzu-An Chen
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Kerry Wong
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
| | - Julie K. Bassett
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
| | - Rachel Murphy
- Centre of Excellence in Cancer Prevention, School of Population & Public Health, Faculty of Medicine, The University of British Columbia, Vancouver, Canada
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt College, Sioux Center, Iowa, United States of America
| | - Chaoyu Ian Yu
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, United States of America
| | - Ingeborg A. Brouwer
- Department of Health Sciences, Faculty of Earth & Life Sciences, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Taiwan
| | - Alexis C. Frazier-Wood
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Liana C. del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Luc Djoussé
- Divisions of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | | | - Graham G. Giles
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Australia
| | - Janette de Goede
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association Research Institute, Holtasmári 1, Kópavogur, Iceland, Iceland
| | - William S. Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, South Dakota, United States of America
- OmegaQuant Analytics LLC, Sioux Falls, South Dakota, United States of America
| | - Allison Hodge
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Australia
| | - Frank Hu
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - InterAct Consortium
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Albert Koulman
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- National Institute for Health Research Biomedical Research Centres Core Nutritional Biomarker Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- National Institute for Health Research Biomedical Research Centres Core Metabolomics and Lipidomics Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- Medical Research Council Elsie Widdowson Laboratory, Cambridge, United Kingdom
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Zhongzheng District, Taipei City, Taiwan
| | - Barbara McKnight
- Department of Biostatistics, University of Washington School of Public Health, Seattle, Washington, United States of America
| | - Kalina Rajaobelina
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - Ulf Risérus
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Sweden
| | - Jennifer G. Robinson
- Departments of Epidemiology and Medicine at the University of Iowa College of Public Health, Iowa City, Iowa, United States of America
| | - Cécilia Samieri
- INSERM, UMR 1219, Bordeaux Population Health Research Center, University of Bordeaux, Bordeaux, France
| | - David S. Siscovick
- The New York Academy of Medicine, New York, New York, United States of America
| | - Sabita S. Soedamah-Muthu
- Division of Human Nutrition, Wageningen University, Wageningen, the Netherlands
- Center of Research on Psychology in Somatic Diseases, Department of Medical and Clinical Psychology, Tilburg University, Tilburg, the Netherlands
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Qi Sun
- Department of Nutrition and Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Michael Y. Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Lynne E. Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Nick J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Jason HY Wu
- The George Institute for Global Health and the Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Rozenn N. Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington, United States of America
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, Massachusetts, United States of America
| | | |
Collapse
|
40
|
Theofylaktopoulou D, Midttun Ø, Ueland PM, Meyer K, Fanidi A, Zheng W, Shu XO, Xiang YB, Prentice R, Pettinger M, Thomson CA, Giles GG, Hodge A, Cai Q, Blot WJ, Wu J, Johansson M, Hultdin J, Grankvist K, Stevens VL, McCullough MM, Weinstein SJ, Albanes D, Ziegler R, Freedman ND, Langhammer A, Hveem K, Næss M, Sesso HD, Gaziano JM, Buring JE, Lee IM, Severi G, Zhang X, Stampfer MJ, Han J, Smith-Warner SA, Zeleniuch-Jacquotte A, le Marchand L, Yuan JM, Wang R, Butler LM, Koh WP, Gao YT, Rothman N, Ericson U, Sonestedt E, Visvanathan K, Jones MR, Relton C, Brennan P, Johansson M, Ulvik A. Impaired functional vitamin B6 status is associated with increased risk of lung cancer. Int J Cancer 2018; 142:2425-2434. [PMID: 29238985 PMCID: PMC5908731 DOI: 10.1002/ijc.31215] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 10/27/2017] [Accepted: 11/22/2017] [Indexed: 12/21/2022]
Abstract
Circulating vitamin B6 levels have been found to be inversely associated with lung cancer. Most studies have focused on the B6 form pyridoxal 5'-phosphate (PLP), a direct biomarker influenced by inflammation and other factors. Using a functional B6 marker allows further investigation of the potential role of vitamin B6 status in the pathogenesis of lung cancer. We prospectively evaluated the association of the functional marker of vitamin B6 status, the 3-hydroxykynurenine:xanthurenic acid (HK:XA) ratio, with risk of lung cancer in a nested case-control study consisting of 5,364 matched case-control pairs from the Lung Cancer Cohort Consortium (LC3). We used conditional logistic regression to evaluate the association between HK:XA and lung cancer, and random effect models to combine results from different cohorts and regions. High levels of HK:XA, indicating impaired functional B6 status, were associated with an increased risk of lung cancer, the odds ratio comparing the fourth and the first quartiles (OR4thvs.1st ) was 1.25 (95% confidence interval, 1.10-1.41). Stratified analyses indicated that this association was primarily driven by cases diagnosed with squamous cell carcinoma. Notably, the risk associated with HK:XA was approximately 50% higher in groups with a high relative frequency of squamous cell carcinoma, i.e., men, former and current smokers. This risk of squamous cell carcinoma was present in both men and women regardless of smoking status.
Collapse
Affiliation(s)
| | | | - Per M. Ueland
- Department of Clinical Science, University of Bergen, Norway
- Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
| | | | - Anouar Fanidi
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - Yong-Bing Xiang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ross Prentice
- Division of Public Health Sciences, Fred Hutchinson Cancer research Center, Seattle, USA
| | - Mary Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer research Center, Seattle, USA
| | - Cynthia A. Thomson
- Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Allison Hodge
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - Jie Wu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, USA
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Johan Hultdin
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Umeå University, Umeå, Sweden
| | | | | | - Stephanie J. Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Regina Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Marit Næss
- HUNT Research Centre, Department of Public Health and Nursing, Faculty of Medicine and Health Science, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Howard D. Sesso
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Division of Aging, Brigham and Women’s Hospital, Boston, MA USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Julie E. Buring
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - I-Min Lee
- Division of Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Gianluca Severi
- Human Genetics Foundation (HuGeF), Torino, Italy
- CESP (U1018 INSERM), Facultés de médecine Université Paris-Sud, UVSQ, Université Paris-Saclay, Villejuif, France
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Meir J. Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiali Han
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Stephanie A. Smith-Warner
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Loic le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania, USA
| | - Lesley M. Butler
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Woon-Puay Koh
- Duke-NUS Medical School, Singapore and Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiaotong University, Shanghai, China
| | - Nathaniel Rothman
- Division of Cancer Epidemiology & Genetics, Occupational and Environmental Epidemiology Branch, National Cancer Institute; Rockville, USA
| | - Ulrika Ericson
- Department of clinical sciences Malmö, Lund University, Sweden
| | - Emily Sonestedt
- Department of clinical sciences Malmö, Lund University, Sweden
| | - Kala Visvanathan
- Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, USA
| | - Miranda R. Jones
- Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, USA
| | - Caroline Relton
- Institute of Genetic Medicine, Newcastle University, Newcastle, UK
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | | |
Collapse
|
41
|
Tan RHH, Hodge A, Klein R, Edwards N, Huang JA, Middleton D, Watts SP. Virus-neutralising antibody responses in horses following vaccination with Equivac® HeV: a field study. Aust Vet J 2018; 96:161-166. [DOI: 10.1111/avj.12694] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 06/23/2017] [Accepted: 08/24/2017] [Indexed: 11/28/2022]
Affiliation(s)
- RHH Tan
- College of Public Health, Medicine and Veterinary Sciences; James Cook University; Townsville Queensland Australia
| | - A Hodge
- Zoetis, Veterinary Medicine Research and Development; Parkville Victoria Australia
| | - R Klein
- CSIRO Australian Animal Health Laboratory; Geelong Victoria Australia
| | - N Edwards
- Wellington Village Veterinary Clinic; Rowville Victoria Australia
| | - JA Huang
- Zoetis, Veterinary Medicine Research and Development; Parkville Victoria Australia
| | - D Middleton
- CSIRO Australian Animal Health Laboratory; Geelong Victoria Australia
| | - SP Watts
- College of Public Health, Medicine and Veterinary Sciences; James Cook University; Townsville Queensland Australia
| |
Collapse
|
42
|
White L, Hodge A, Vlok R, Hurtado G, Eastern K, Melhuish T. Efficacy and adverse effects of buprenorphine in acute pain management: systematic review and meta-analysis of randomised controlled trials. Br J Anaesth 2018; 120:668-678. [DOI: 10.1016/j.bja.2017.11.086] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Revised: 08/24/2017] [Accepted: 08/30/2017] [Indexed: 10/18/2022] Open
|
43
|
Clough WJ, Little PR, Hodge A, Chapman VC, Holz DK. Protection of sheep by vaccination against experimental challenge with Leptospira borgpetersenii serovar Hardjo and L. interrogans serovar Pomona. N Z Vet J 2018; 66:138-143. [PMID: 29457991 DOI: 10.1080/00480169.2018.1441078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
AIMS To evaluate a multivalent leptospiral and clostridial vaccine for prevention of renal colonisation and urinary shedding in sheep, following experimental challenge with New Zealand strains of Leptospira borgpetersenii serovar Hardjo type Hardjobovis and L. interrogans serovar Pomona. METHODS Two separate but similarly designed studies were conducted. In both studies, Romney-cross lambs, aged 9-11 weeks, were randomly allocated to a vaccinated group and a control group. Vaccinated lambs each received two 1.5-mL S/C doses of a multivalent leptospiral and clostridial vaccine, 4 weeks apart, and animals in the control groups received the same dose of saline. Groups of 12 vaccinated and 12 control lambs were randomly selected in each study for challenge with serovars Hardjo or Pomona. Challenge was initiated 16 weeks following the second vaccination with three daily doses of live leptospires by intranasal and conjunctival routes. Following challenge, urine samples were collected weekly for 6 weeks, for dark field microscopy and leptospiral culture; 6 weeks after challenge the lambs were slaughtered and kidneys collected for leptospiral culture. RESULTS In lambs challenged with serovar Hardjo, 8/12 unvaccinated lambs had ≥1 urine or kidney sample that was positive for leptospires following culture, compared with 0/12 lambs in the vaccinated group (p=0.001). In lambs challenged with serovar Pomona, 9/12 unvaccinated lambs had ≥1 urine or kidney sample that was positive following culture, compared with 0/12 lambs in the vaccinated group (p<0.001). Prevention of renal colonisation and urinary shedding, expressed as the prevented fraction, was 100 (95% CI=61.7-100)% and 100 (95% CI=68.3-100)% against challenge with serovars Hardjo and Pomona, respectively, at 4 months after vaccination. CONCLUSIONS AND CLINICAL RELEVANCE Use of a multivalent leptospiral and clostridial vaccine demonstrated protection against challenge from New Zealand strains of serovars of Hardjo and Pomona 4 months after vaccination in lambs first vaccinated at 9-11 weeks of age. Further studies are required to assess the duration of immunity against challenge in sheep.
Collapse
Affiliation(s)
- W J Clough
- a Zoetis New Zealand Ltd , PO Box 2094, Shortland Street, Auckland , 1140 , New Zealand
| | - P R Little
- b Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW , 2138 , Australia
| | - A Hodge
- b Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW , 2138 , Australia
| | - V C Chapman
- a Zoetis New Zealand Ltd , PO Box 2094, Shortland Street, Auckland , 1140 , New Zealand
| | - D K Holz
- a Zoetis New Zealand Ltd , PO Box 2094, Shortland Street, Auckland , 1140 , New Zealand
| |
Collapse
|
44
|
Shang X, Scott D, Hodge A, English DR, Giles GG, Ebeling PR, Sanders KM. Dietary protein from different food sources, incident metabolic syndrome and changes in its components: An 11-year longitudinal study in healthy community-dwelling adults. Clin Nutr 2017; 36:1540-1548. [DOI: 10.1016/j.clnu.2016.09.024] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Revised: 09/16/2016] [Accepted: 09/23/2016] [Indexed: 11/27/2022]
|
45
|
Wu JHY, Marklund M, Imamura F, Tintle N, Ardisson Korat AV, de Goede J, Zhou X, Yang WS, de Oliveira Otto MC, Kröger J, Qureshi W, Virtanen JK, Bassett JK, Frazier-Wood AC, Lankinen M, Murphy RA, Rajaobelina K, Del Gobbo LC, Forouhi NG, Luben R, Khaw KT, Wareham N, Kalsbeek A, Veenstra J, Luo J, Hu FB, Lin HJ, Siscovick DS, Boeing H, Chen TA, Steffen B, Steffen LM, Hodge A, Eriksdottir G, Smith AV, Gudnason V, Harris TB, Brouwer IA, Berr C, Helmer C, Samieri C, Laakso M, Tsai MY, Giles GG, Nurmi T, Wagenknecht L, Schulze MB, Lemaitre RN, Chien KL, Soedamah-Muthu SS, Geleijnse JM, Sun Q, Harris WS, Lind L, Ärnlöv J, Riserus U, Micha R, Mozaffarian D. Omega-6 fatty acid biomarkers and incident type 2 diabetes: pooled analysis of individual-level data for 39 740 adults from 20 prospective cohort studies. Lancet Diabetes Endocrinol 2017; 5:965-974. [PMID: 29032079 PMCID: PMC6029721 DOI: 10.1016/s2213-8587(17)30307-8] [Citation(s) in RCA: 196] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 08/01/2017] [Accepted: 08/04/2017] [Indexed: 12/23/2022]
Abstract
BACKGROUND The metabolic effects of omega-6 polyunsaturated fatty acids (PUFAs) remain contentious, and little evidence is available regarding their potential role in primary prevention of type 2 diabetes. We aimed to assess the associations of linoleic acid and arachidonic acid biomarkers with incident type 2 diabetes. METHODS We did a pooled analysis of new, harmonised, individual-level analyses for the biomarkers linoleic acid and its metabolite arachidonic acid and incident type 2 diabetes. We analysed data from 20 prospective cohort studies from ten countries (Iceland, the Netherlands, the USA, Taiwan, the UK, Germany, Finland, Australia, Sweden, and France), with biomarkers sampled between 1970 and 2010. Participants included in the analyses were aged 18 years or older and had data available for linoleic acid and arachidonic acid biomarkers at baseline. We excluded participants with type 2 diabetes at baseline. The main outcome was the association between omega-6 PUFA biomarkers and incident type 2 diabetes. We assessed the relative risk of type 2 diabetes prospectively for each cohort and lipid compartment separately using a prespecified analytic plan for exposures, covariates, effect modifiers, and analysis, and the findings were then pooled using inverse-variance weighted meta-analysis. FINDINGS Participants were 39 740 adults, aged (range of cohort means) 49-76 years with a BMI (range of cohort means) of 23·3-28·4 kg/m2, who did not have type 2 diabetes at baseline. During a follow-up of 366 073 person-years, we identified 4347 cases of incident type 2 diabetes. In multivariable-adjusted pooled analyses, higher proportions of linoleic acid biomarkers as percentages of total fatty acid were associated with a lower risk of type 2 diabetes overall (risk ratio [RR] per interquintile range 0·65, 95% CI 0·60-0·72, p<0·0001; I2=53·9%, pheterogeneity=0·002). The associations between linoleic acid biomarkers and type 2 diabetes were generally similar in different lipid compartments, including phospholipids, plasma, cholesterol esters, and adipose tissue. Levels of arachidonic acid biomarker were not significantly associated with type 2 diabetes risk overall (RR per interquintile range 0·96, 95% CI 0·88-1·05; p=0·38; I2=63·0%, pheterogeneity<0·0001). The associations between linoleic acid and arachidonic acid biomarkers and the risk of type 2 diabetes were not significantly modified by any prespecified potential sources of heterogeneity (ie, age, BMI, sex, race, aspirin use, omega-3 PUFA levels, or variants of the FADS gene; all pheterogeneity≥0·13). INTERPRETATION Findings suggest that linoleic acid has long-term benefits for the prevention of type 2 diabetes and that arachidonic acid is not harmful. FUNDING Funders are shown in the appendix.
Collapse
Affiliation(s)
- Jason H Y Wu
- The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
| | - Matti Marklund
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Fumiaki Imamura
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Nathan Tintle
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA
| | - Andres V Ardisson Korat
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Janette de Goede
- Division of Human Nutrition, Wageningen University, Wageningen, Netherlands
| | - Xia Zhou
- School of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Wei-Sin Yang
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Marcia C de Oliveira Otto
- Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center, School of Public Health, Houston, TX, USA
| | - Janine Kröger
- German Institute of Human Nutrition, Potsdam, Germany
| | | | - Jyrki K Virtanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | - Alexis C Frazier-Wood
- US Department of Agriculture/Agricultural Research Service, Children's Nutrition Research Center, Houston, TX, USA
| | - Maria Lankinen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | - Kalina Rajaobelina
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Liana C Del Gobbo
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nita G Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Robert Luben
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA
| | - Nick Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Anya Kalsbeek
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA; Department of Biology, Dordt College, Sioux Center, IA, USA
| | - Jenna Veenstra
- Department of Mathematics and Statistics, Dordt College, Sioux Center, IA, USA; Department of Biology, Dordt College, Sioux Center, IA, USA
| | - Juhua Luo
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN, USA
| | - Frank B Hu
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hung-Ju Lin
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | | | - Heiner Boeing
- German Institute of Human Nutrition, Potsdam, Germany
| | - Tzu-An Chen
- US Department of Agriculture/Agricultural Research Service, Children's Nutrition Research Center, Houston, TX, USA
| | - Brian Steffen
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Lyn M Steffen
- School of Public Health, Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | | | | | | | | | | | | | - Claudine Berr
- INSERM U1061, Neuropsychiatry: Epidemiological and Clinical Research, and Montpellier University Hospital, Montpellier University, Montpellier, France
| | - Catherine Helmer
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Cecilia Samieri
- University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, UMR 1219, Bordeaux, France
| | - Markku Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Michael Y Tsai
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | | | - Tarja Nurmi
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | | | | | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Kuo-Liong Chien
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | | | | | - Qi Sun
- Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - William S Harris
- Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, USA; OmegaQuant Analytics, Sioux Falls, SD, USA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Johan Ärnlöv
- Department of Neurobiology, Care Sciences and Society, Division of Family Medicine, Karolinska Institute, Stockholm, Sweden; School of Health and Social Studies, Dalarna University, Falun, Sweden
| | - Ulf Riserus
- Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden
| | - Renata Micha
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
| |
Collapse
|
46
|
Simapivapan P, Hodge A, Boltong A. Exploring the provision of alcohol advice by clinicians to breast cancer patients. Eur J Cancer Care (Engl) 2017; 27. [PMID: 28745015 DOI: 10.1111/ecc.12739] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/26/2017] [Indexed: 12/16/2022]
Abstract
Interactions between clinicians and patients along the cancer trajectory provide an opportunity to deliver key messages regarding drinking behaviours and long-term health. This study aimed to explore the extent and nature of clinician-patient discussions regarding alcohol intake and cancer outcomes in the clinical breast cancer setting, using a qualitative research design involving semi-structured interviews. Purposive sampling was used to recruit 27 breast cancer clinicians (eight dietitians, nine breast care nurses, 10 oncologists) across Victoria, Australia. Interview data were analysed using descriptive statistics and a content analysis approach. Clinicians' knowledge of national alcohol recommendations was found to be inconsistent. Clinicians reported a lack of patient awareness of the link between alcohol and breast cancer. Current frameworks for assessing and advising on patient alcohol intake were felt to be impractical. The extent and nature of advice provided about alcohol was influenced by several patient and clinician factors. The provision of alcohol advice in the clinical breast cancer setting is not practiced systematically by any professional group. New approaches are needed to support patient education about alcohol intake and survivorship in the clinical oncology setting.
Collapse
Affiliation(s)
- P Simapivapan
- The University of Melbourne, Parkville, Vic., Australia
| | - A Hodge
- The University of Melbourne, Parkville, Vic., Australia.,Cancer Council Victoria, Melbourne, Vic., Australia
| | - A Boltong
- The University of Melbourne, Parkville, Vic., Australia.,Cancer Council Victoria, Melbourne, Vic., Australia
| |
Collapse
|
47
|
Rodríguez AJ, Scott D, Hodge A, English DR, Giles GG, Ebeling PR. Associations between hip bone mineral density, aortic calcification and cardiac workload in community-dwelling older Australians. Osteoporos Int 2017; 28:2239-2245. [PMID: 28378290 DOI: 10.1007/s00198-017-4024-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2016] [Accepted: 03/27/2017] [Indexed: 10/19/2022]
Abstract
UNLABELLED In older adults, lower bone density in the proximal femur was associated with increased heart burden, and this association was linked to calcification in the aorta. These results were seen in women but not in men. PURPOSE To determine whether there is an association between lower bone mineral density (BMD) and increased cardiac workload in older adults, and if this association was independent of abdominal aortic calcification (AAC). METHODS Three hundred thirty-seven participants [mean ± SD age = 70 ± 5 years and BMI = 28 ± 5 kg/m2, 61% females] had BMD determined by dual-energy X-ray absorptiometry and AAC determined by radiography. Aortic calcification score (ACS) was determined visually in the L1-L4 vertebrae (range 0-24). Systolic blood pressure (BP) and heart rate (HR) were measured. The rate pressure product (RPP), a measure of cardiac workload, was determined by multiplying BP and HR. RESULTS AAC was present in 205 (61%) participants. Mean ± SD RPP was 9120 ± 1823; range was 5424-18,537. In all participants, ACS was positively associated with log-transformed RPP [LnRPP] (β = 0.011, p < 0.001), and severe calcification was positively associated with LnRPP (β = 0.083, p = 0.004 relative to no calcification). In sex-stratified analyses, these associations were significant only in females. Lower odds of any AAC were observed per 1 g/cm2 increment in femoral neck BMD (OR = 0.08, 95% CI 0.01-0.95). A similar trend was evident in women separately (OR = 0.05, 95% CI 0-1.17) but not men. In all participants, femoral neck (β = -0.20, p = 0.04) and total hip BMD (β = -0.17, p = 0.04) were inversely associated with LnRPP after multivariate adjustment. Adjusting additionally for AAC reduced the strength of the association in femoral neck (β = -0.19, p = 0.05) but not total hip BMD (β = -0.17, p = 0.04). CONCLUSION Lower BMD was marginally, but significantly with increased LnRPP, and this relationship was partially mediated by AAC suggesting that older adults, particularly females, with osteoporosis may have an increased cardiovascular risk.
Collapse
Affiliation(s)
- A J Rodríguez
- Bone and Muscle Health Research Group, Department of Medicine, School of Clinical Sciences at Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Monash Medical Centre, 246 Clayton Road, Clayton, VIC, 3146, Australia.
| | - D Scott
- Bone and Muscle Health Research Group, Department of Medicine, School of Clinical Sciences at Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Monash Medical Centre, 246 Clayton Road, Clayton, VIC, 3146, Australia
- Melbourne Medical School (Western Campus), University of Melbourne, St Albans, Australia
- Australian Institute for Musculoskeletal Science, St Albans, Australia
| | - A Hodge
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, 3052, Australia
| | - D R English
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, 3052, Australia
| | - G G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, 3004, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, 3052, Australia
| | - P R Ebeling
- Bone and Muscle Health Research Group, Department of Medicine, School of Clinical Sciences at Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Monash Medical Centre, 246 Clayton Road, Clayton, VIC, 3146, Australia
- Melbourne Medical School (Western Campus), University of Melbourne, St Albans, Australia
- Australian Institute for Musculoskeletal Science, St Albans, Australia
| |
Collapse
|
48
|
Midttun Ø, Theofylaktopoulou D, McCann A, Fanidi A, Muller DC, Meyer K, Ulvik A, Zheng W, Shu XO, Xiang YB, Prentice R, Thomson CA, Pettinger M, Giles GG, Hodge A, Cai Q, Blot WJ, Wu J, Johansson M, Hultdin J, Grankvist K, Stevens VL, McCullough ML, Weinstein SJ, Albanes D, Langhammer A, Hveem K, Næss M, Sesso HD, Gaziano JM, Buring JE, Lee IM, Severi G, Zhang X, Han J, Stampfer MJ, Smith-Warner SA, Zeleniuch-Jacquotte A, le Marchand L, Yuan JM, Butler LM, Koh WP, Wang R, Gao YT, Ericson U, Sonestedt E, Ziegler RG, Freedman ND, Visvanathan K, Jones MR, Relton C, Brennan P, Johansson M, Ueland PM. Circulating concentrations of biomarkers and metabolites related to vitamin status, one-carbon and the kynurenine pathways in US, Nordic, Asian, and Australian populations. Am J Clin Nutr 2017; 105:1314-1326. [PMID: 28424186 PMCID: PMC5445679 DOI: 10.3945/ajcn.116.151241] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 03/16/2017] [Indexed: 12/21/2022] Open
Abstract
Background: Circulating concentrations of biomarkers that are related to vitamin status vary by factors such as diet, fortification, and supplement use. Published biomarker concentrations have also been influenced by the variation across laboratories, which complicates a comparison of results from different studies.Objective: We robustly and comprehensively assessed differences in biomarkers that are related to vitamin status across geographic regions.Design: The trial was a cross-sectional study in which we investigated 38 biomarkers that are related to vitamin status and one-carbon and tryptophan metabolism in serum and plasma from 5314 healthy control subjects representing 20 cohorts recruited from the United States, Nordic countries, Asia, and Australia, participating in the Lung Cancer Cohort Consortium. All samples were analyzed in a centralized laboratory.Results: Circulating concentrations of riboflavin, pyridoxal 5'-phosphate, folate, vitamin B-12, all-trans retinol, 25-hydroxyvitamin D, and α-tocopherol as well as combined vitamin scores that were based on these nutrients showed that the general B-vitamin concentration was highest in the United States and that the B vitamins and lipid soluble vitamins were low in Asians. Conversely, circulating concentrations of metabolites that are inversely related to B vitamins involved in the one-carbon and kynurenine pathways were high in Asians. The high B-vitamin concentration in the United States appears to be driven mainly by multivitamin-supplement users.Conclusions: The observed differences likely reflect the variation in intake of vitamins and, in particular, the widespread multivitamin-supplement use in the United States. The results provide valuable information about the differences in biomarker concentrations in populations across continents.
Collapse
Affiliation(s)
| | | | | | - Anouar Fanidi
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - David C Muller
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom
| | | | | | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ross Prentice
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Cynthia A Thomson
- Health Promotion Sciences, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - Mary Pettinger
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Graham G Giles
- Cancer Epidemiology Center, Cancer Council Victoria, Melbourne, Victoria, Australia
- Center for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Allison Hodge
- Cancer Epidemiology Center, Cancer Council Victoria, Melbourne, Victoria, Australia
- Center for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
- International Epidemiology Institute, Rockville, MD
| | - Jie Wu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN
| | | | - Johan Hultdin
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | | | | | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD
| | - Arnulf Langhammer
- Nord-Trøndelag Health Study Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Levanger, Norway
| | - Kristian Hveem
- Nord-Trøndelag Health Study Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Levanger, Norway
| | - Marit Næss
- Nord-Trøndelag Health Study Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Levanger, Norway
| | - Howard D Sesso
- Divisions of Preventive Medicine and
- Aging, Brigham and Women's Hospital, Boston, MA
- Departments of Epidemiology and
| | - J Michael Gaziano
- Aging, Brigham and Women's Hospital, Boston, MA
- VA Boston Healthcare System, Boston, MA
| | - Julie E Buring
- Divisions of Preventive Medicine and
- Departments of Epidemiology and
| | - I-Min Lee
- Divisions of Preventive Medicine and
- Departments of Epidemiology and
| | - Gianluca Severi
- Human Genetics Foundation, Turin, Italy
- Centre for Research in Epidemiology and Population Health (U1018 French National Institute of Health and Medical Research), Facultés de Médecine Université Paris-Sud, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, Villejuif, France
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | | | - Meir J Stampfer
- Departments of Epidemiology and
- Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | | | | | - Loic le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, PA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Lesley M Butler
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, PA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Woon-Puay Koh
- Duke-National University of Singapore (NSU) Medical School, Singapore, and Saw Swee Hock School of Public Health, NSU, Singapore, Singapore
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, University of Pittsburgh Cancer Institute, Pittsburgh, PA
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiaotong University, Shanghai, China
| | - Ulrika Ericson
- Department of clinical sciences Malmö, Lund University, Lund, Sweden
| | - Emily Sonestedt
- Department of clinical sciences Malmö, Lund University, Lund, Sweden
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD
| | - Kala Visvanathan
- Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, Baltimore, MD
| | - Miranda R Jones
- Johns Hopkins Bloomberg School of Public Health and Johns Hopkins Sidney Kimmel Comprehensive Center, School of Medicine, Baltimore, MD
| | - Caroline Relton
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
- Medical Research Council Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom; and
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Per M Ueland
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
| |
Collapse
|
49
|
Marti S, Jackson J, Slootmans N, Lopez E, Hodge A, Pérez-Juan M, Devant M, Amatayakul-Chantler S. Effects on performance and meat quality of Holstein bulls fed high concentrate diets without implants following immunological castration. Meat Sci 2017; 126:36-42. [DOI: 10.1016/j.meatsci.2016.11.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2016] [Revised: 11/16/2016] [Accepted: 11/17/2016] [Indexed: 10/20/2022]
|
50
|
Packianathan R, Clough WJ, Hodge A, Holz DK, Huang J, Bryant GL, Colantoni C. Prevention of fetal infection in heifers challenged with bovine viral diarrhoea virus type 1a by vaccination with a type 1c or type 1a vaccine. N Z Vet J 2017; 65:134-139. [PMID: 28359226 DOI: 10.1080/00480169.2017.1291376] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
AIMS To evaluate a vaccine containing type 1c bovine viral diarrhoea (BVD) virus for prevention of fetal infection in pregnant heifers when challenged with New Zealand BVD virus type 1a 6 months after vaccination, compared to unvaccinated heifers and heifers vaccinated with a vaccine containing type 1a BVD virus. METHODS Fifty five crossbred Friesian heifers, free from BVD virus and antibody, were randomly allocated to three groups. Twenty five heifers were vaccinated twice with a vaccine containing type 1c BVD virus (T1c group), and 10 heifers with a vaccine containing type 1a BVD virus (T1a group), and 20 heifers were unvaccinated (NC group). After oestrus synchronisation the heifers were bred by artificial insemination followed by natural bull mating. Six months after booster vaccination 15 heifers from the T1c group, eight from the T1a group, and 15 from the NC group, were exposed to four calves that were persistently infected with type 1a BVD virus, for 4 weeks. At the beginning of the challenge phase 36/38 heifers were 72-74 days pregnant and 2/38 heifers were approximately 53 days pregnant. Approximately 52 days after the start of the challenge the heifers were subjected to euthanasia and fetal tissues were collected for the detection of BVD virus by ELISA in fetal heart blood and PCR in fetal tissues. RESULTS Based on PCR results, BVD virus was detected in 15/15 fetuses in the NC group, compared to 4/14 fetuses in the T1c group and 3/8 fetuses in the T1a group. The proportion of BVD virus-positive fetuses was lower in both vaccinated groups compared to the NC group (p<0.002), but there was no difference in proportions between the vaccinated groups (p=1.00). Fetal protection, expressed as the prevented fraction, was 71.4 (95% CI=41.9-91.6)% and 62.5 (95% CI=24.5-91.5)% for the T1c and T1a groups, respectively. CONCLUSIONS AND CLINICAL RELEVANCE The vaccines containing killed type 1c and type 1a BVD viruses significantly reduced fetal infection following challenge with a New Zealand type 1a BVD virus. Prevention of fetal infection by vaccination may not be 100%, and the risk of persistently infected calves being born to some vaccinated cattle should be acknowledged and managed as part of a BVD control programme.
Collapse
Affiliation(s)
- R Packianathan
- a Veterinary Medicines Research and Development , Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW 2138 , Australia
| | - W J Clough
- b Zoetis New Zealand Ltd , PO Box 2094, Shortland Street, Auckland , 1140 , New Zealand
| | - A Hodge
- a Veterinary Medicines Research and Development , Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW 2138 , Australia
| | - D K Holz
- b Zoetis New Zealand Ltd , PO Box 2094, Shortland Street, Auckland , 1140 , New Zealand
| | - J Huang
- a Veterinary Medicines Research and Development , Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW 2138 , Australia
| | - G L Bryant
- a Veterinary Medicines Research and Development , Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW 2138 , Australia
| | - C Colantoni
- a Veterinary Medicines Research and Development , Zoetis Australia Research and Manufacturing Pty Ltd , Level 6, 5 Rider Boulevard, Rhodes , NSW 2138 , Australia
| |
Collapse
|