1
|
Whatnall M, Clarke ED, Adam MTP, Ashton LM, Burrows T, Hutchesson M, Collins CE. Diet Quality of Adolescents and Adults Who Completed the Australian Healthy Eating Quiz: An Analysis of Data over Six Years (2016-2022). Nutrients 2022; 14:nu14194072. [PMID: 36235723 PMCID: PMC9570644 DOI: 10.3390/nu14194072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/28/2022] [Accepted: 09/29/2022] [Indexed: 11/16/2022] Open
Abstract
Diet quality is influenced by demographics and can change over time. This study aimed to (1) compare diet quality among adolescents/adults who completed the online Healthy Eating Quiz (HEQ) by demographic characteristics, and (2) to evaluate change in score over time for repeat completers. HEQ data collected between July 2016 and May 2022 were analysed, including demographics (age, gender, vegetarian status, socio-economic status, number of people main meals are shared with, country), and diet quality calculated using the Australian Recommended Food Score (ARFS) (range 0−73) for respondents aged ≥ 16 years. Differences in ARFS by demographic characteristics and change in score over time, adjusted for age, gender and vegetarian status, were tested by linear regression. The participants (n = 176,075) were predominantly female (70.4%), Australian (62.8%), and aged 18−24 years (27.7%), with 4.0% (n = 7087) repeat completers. Mean ± SD ARFS was 33.9 ± 9.4/73. Results indicate that ARFS was significantly lower among males and significantly higher with increasing age group, higher socio-economic status, in vegetarians, those who shared main meals with others, and those living in Australia (p-values < 0.001). Mean change in ARFS over time (2.3 ± 6.9) was significantly higher for those with lower baseline scores (p < 0.001). Publicly available, brief dietary assessment tools have the potential to improve diet quality at the population level.
Collapse
Affiliation(s)
- Megan Whatnall
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
| | - Erin D. Clarke
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
| | - Marc T. P. Adam
- School of Information and Physical Sciences, College of Engineering, Science and Environment, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
| | - Lee M. Ashton
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- School of Education, College of Human and Social Futures, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Active Living Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
| | - Tracy Burrows
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
| | - Melinda Hutchesson
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
| | - Clare E. Collins
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Newcastle, NSW 2308, Australia
- Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW 2305, Australia
- Correspondence:
| |
Collapse
|
2
|
Somerville M, Ball L, Kirkegaard A, Williams LT. How do patients want to receive nutrition care? Qualitative findings from Australian health consumers. Aust J Prim Health 2021; 28:33-39. [PMID: 34911618 DOI: 10.1071/py21077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 09/22/2021] [Indexed: 11/23/2022]
Abstract
This qualitative descriptive study explored health consumers' preferences for receiving nutrition care in Australian primary care. The study was underpinned by a constructivist research paradigm. Semistructured telephone interviews were conducted with 25 health consumers (age 19-78 years; 19 female) from across Australia between May and August 2020. Content analysis, using an inductive approach revealed emergent themes. was used to reveal emergent themes. Five themes were identified in the data: (1) health consumers want to receive nutrition care from a qualified person; (2) nutrition care is viewed as important, and health consumers want to receive it in a format that meets their needs; (3) nutrition care should be low cost and available to everyone; (4) nutrition care services should be conveniently located; and (5) health consumers want nutrition care to be offered frequently, across their lifespan. Health consumers have a clear idea of how they would like to receive nutrition care in the primary care setting, but reported challenges to receiving this care within the current system. New models of service delivery are needed to meet the needs of health consumers.
Collapse
Affiliation(s)
- Mari Somerville
- Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, Qld 4222, Australia; and Corresponding author
| | - Lauren Ball
- Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, Qld 4222, Australia
| | - Amy Kirkegaard
- Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, Qld 4222, Australia
| | - Lauren T Williams
- Menzies Health Institute Queensland, Griffith University, Gold Coast Campus, Parklands Drive, Gold Coast, Qld 4222, Australia
| |
Collapse
|
3
|
Baldwin JN, Ashton LM, Forder PM, Haslam RL, Hure AJ, Loxton DJ, Patterson AJ, Collins CE. Increasing Fruit and Vegetable Variety over Time Is Associated with Lower 15-Year Healthcare Costs: Results from the Australian Longitudinal Study on Women's Health. Nutrients 2021; 13:2829. [PMID: 34444989 PMCID: PMC8398554 DOI: 10.3390/nu13082829] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 08/11/2021] [Accepted: 08/14/2021] [Indexed: 01/04/2023] Open
Abstract
Healthcare costs are lower for adults who consume more vegetables; however, the association between healthcare costs and fruit and vegetable varieties is unclear. Our aim was to investigate the association between (i) baseline fruit and vegetable (F&V) varieties, and (ii) changes in F&V varieties over time with 15-year healthcare costs in an Australian Longitudinal Study on Women's Health. The data for Survey 3 (n = 8833 women, aged 50-55 years) and Survey 7 (n = 6955, aged 62-67 years) of the 1946-1951 cohort were used. The F&V variety was assessed using the Fruit and Vegetable Variety (FAVVA) index calculated from the Cancer Council of Victoria's Dietary Questionnaire for Epidemiological Studies food frequency questionnaire. The baseline FAVVA and change in FAVVA were analysed as continuous predictors of Medicare claims/costs by using multiple regression analyses. Healthy weight women made, on average, 4.3 (95% confidence interval (CI) 1.7-6.8) fewer claims for every 10-point-higher FAVVA. Healthy weight women with higher fruit varieties incurred fewer charges; however, this was reversed for women overweight/obese. Across the sample, for every 10-point increase in FAVVA over time, women made 4.3 (95% CI 1.9-6.8) fewer claims and incurred $309.1 (95% CI $129.3-488.8) less in charges over 15 years. A higher F&V variety is associated with a small reduction in healthcare claims for healthy weight women only. An increasing F&V variety over time is associated with lower healthcare costs.
Collapse
Affiliation(s)
- Jennifer N. Baldwin
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (L.M.A.); (R.L.H.); (A.J.P.)
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Lee M. Ashton
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (L.M.A.); (R.L.H.); (A.J.P.)
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Peta M. Forder
- Priority Research Centre for Generational Health and Ageing, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
| | - Rebecca L. Haslam
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (L.M.A.); (R.L.H.); (A.J.P.)
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Alexis J. Hure
- Priority Research Centre for Generational Health and Ageing, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW 2305, Australia
| | - Deborah J. Loxton
- Priority Research Centre for Generational Health and Ageing, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
| | - Amanda J. Patterson
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (L.M.A.); (R.L.H.); (A.J.P.)
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Clare E. Collins
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (L.M.A.); (R.L.H.); (A.J.P.)
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia
| |
Collapse
|
4
|
Andrew NE, Cadilhac DA, Sundararajan V, Thrift AG, Anderson P, Lannin NA, Kilkenny MF. Linking Australian Stroke Clinical Registry data with Australian government Medicare and medication dispensing claims data and the potential for bias. Aust N Z J Public Health 2021; 45:364-369. [PMID: 33818854 DOI: 10.1111/1753-6405.13079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 11/01/2020] [Accepted: 12/01/2020] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE We aim to report the accuracy of linking data from a non-government-held clinical quality registry to national claims data and identify associated sources of systematic bias. METHODS Patients with stroke or transient ischaemic attack admitted to hospitals participating in the Australian Stroke Clinical Registry (AuSCR) were linked with Medicare and medication dispensings through the Australian Medicare enrolment file (MEF). The proportion of registrants in the datasets was calculated and factors associated with a non-merge assessed using multivariable analyses. RESULTS A total of 17,980 AuSCR registrants (January 2010 - July 2014) were submitted for linkage (median age 76 years; 46% female; 67% ischaemic stroke); the proportion merged was 97% MEF, 93% Medicare and 95% medication dispensings. Data from registrants born in Asia were less likely to link with the MEF (adjusted Odds Ratio [aOR]: 0.20; 95%Confidence Interval [CI]: 0.15, 0.27). Data for those aged 85-plus compared to those under 65 years were less likely to merge with Medicare (aOR 0.25; 95%CI:0.21, 0.30) but more likely to merge with dispensing claims data (aOR: 2.15 (95%CI:1.71, 2.69). Implications for public health: Linkage between the AuSCR, a national clinical quality registry and Commonwealth datasets was achieved and potential sources of bias were identified.
Collapse
Affiliation(s)
- Nadine E Andrew
- Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria.,Peninsula Clinical School, Central Clinical School, Monash University, Victoria
| | - Dominique A Cadilhac
- Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria.,Florey Institute of Neuroscience and Mental Health, Victoria
| | - Vijaya Sundararajan
- Department of Public Health, School of Psychology and Public Health, College of Science, Health and Engineering, La Trobe University, Victoria
| | - Amanda G Thrift
- Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria
| | - Phil Anderson
- Health Linkage Unit, Australian Institute of Health and Welfare, Australian Capital Territory.,Faculty of Health, University of Canberra, Australian Capital Territory
| | - Natasha A Lannin
- Department of Neuroscience, Central Clinical School, Monash University, Victoria.,Alfred Health (Allied Health), Victoria
| | - Monique F Kilkenny
- Stroke & Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Victoria.,Florey Institute of Neuroscience and Mental Health, Victoria
| |
Collapse
|
5
|
Lower Vegetable Variety and Worsening Diet Quality Over Time Are Associated With Higher 15-Year Health Care Claims and Costs Among Australian Women. J Acad Nutr Diet 2021; 121:655-668. [PMID: 33487591 DOI: 10.1016/j.jand.2020.12.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 11/30/2020] [Accepted: 12/15/2020] [Indexed: 11/21/2022]
Abstract
BACKGROUND The relationship between diet quality and health care costs is unclear. OBJECTIVE The aim of this study was to investigate the relationship between baseline diet quality and change in diet quality over time, with 15-year cumulative health care claims/costs. DESIGN Data from a longitudinal cohort study were analyzed. PARTICIPANTS/SETTING Data for survey 3 (2001) (n = 7,868) and survey 7 (2013) (n = 6,349 both time points) from the 1946-1951 cohort of the Australian Longitudinal Study on Women's Health were analyzed. MAIN OUTCOME MEASURES Diet quality was assessed using the Australian Recommended Food Score (ARFS). Fifteen-year cumulative Medicare Benefits Schedule (Australia's universal health care coverage) data were reported by baseline ARFS quintile and category of diet quality change ("diet quality worsened" [ARFS change ≤ -4 points], "remained stable" [-3 ≤ change in ARFS ≤3 points], or "improved" [ARFS change ≥4 points]). STATISTICAL ANALYSES Linear regression analyses were conducted adjusting for area of residence, socioeconomic status, lifestyle factors, and private health insurance status. RESULTS Consuming a greater variety of vegetables at baseline but fewer fruit and dairy products was associated with lower health care costs. For every 1-point increment in the ARFS vegetable subscale, women made 3.3 (95% CI, 1.6-5.0) fewer claims and incurred AU$227 (95% CI, AU$104-350 [US$158; 95% CI, US$72-243]) less in costs. Women whose diet quality worsened over time made more claims (median, 251 claims; quintile 1, quintile 3 [Q1; Q3], 168; 368 claims) and incurred higher costs (AU$15,519; Q1; Q3, AU$9,226; AU$24,847 [US$10,793; Q1; Q3, US$6,417; US$17,281]) compared with those whose diet quality remained stable (median, 236 claims [Q1; Q3, 158; 346 claims], AU$14,515; Q1; Q3, AU$8,539; AU$23,378 [US$10,095; Q1; Q3, US$5,939; US$16,259]). CONCLUSIONS Greater vegetable variety was associated with fewer health care claims and costs; however, this trend was not consistent across other subscales. Worsening diet quality over 12 years was linked with higher health care claims and costs.
Collapse
|
6
|
Fenton S, Burrows TL, Skinner JA, Duncan MJ. The influence of sleep health on dietary intake: a systematic review and meta-analysis of intervention studies. J Hum Nutr Diet 2020; 34:273-285. [PMID: 33001515 DOI: 10.1111/jhn.12813] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 07/28/2020] [Accepted: 08/22/2020] [Indexed: 01/07/2023]
Abstract
BACKGROUND Poor dietary intake increases disease risk, and poor sleep influences diet. This systematic review and meta-analysis of intervention studies aimed to evaluate the effect of sleep health on dietary intake in adults. METHODS Five online databases were used to identify studies published between 1970 and 2019. Included studies were interventions that modified sleep and reported dietary outcomes. RESULTS Fifty four full texts were assessed and 24 publications were included. Following risk of bias appraisal, data were narratively summarised and a sub-group of studies (n = 15) was meta-analysed to determine the effect of sleep on dietary intake. One intervention modified sleep timing and 23 modified duration. Sleep duration was partially restricted (≤5.5 h night-1 ) (n = 16), totally restricted (n = 4), partially and totally restricted (n = 1), and extended (n = 2). Dietary outcomes were energy intake (n = 24), carbohydrate, fat, protein intake (n = 20), single nutrient intake (n = 5), diet quality (n = 1) and food types (n = 1). Meta-analysis indicated partial sleep restriction results in higher energy intake in intervention compared with control [standardised mean difference (SMD) = 0.37; 95% confidence interval (CI) = 0.21-0.52; P < 0.001], with a mean difference of 204 kcal (95% CI = 112-295; P < 0.001) in daily energy intake, and a higher percentage of energy from fat, protein, carbohydrate (fat: SMD = 0.33; 95% CI = 0.16-0.51; P < 0.001; protein: SMD = 0.30, 95% CI = 0.12-0.47, P = 0.001; carbohydrate: SMD = 0.22, 95% CI = 0.04-0.39, P = 0.014). CONCLUSIONS Partial sleep restriction with duration of ≤5.5 h day-1 increases daily energy intake, as well as fat, protein and carbohydrate intake. Further research is needed to determine the relationship between other dimensions of sleep health and dietary intake.
Collapse
Affiliation(s)
- S Fenton
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia.,Faculty of Health and Medicine, School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
| | - T L Burrows
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia.,Faculty of Health and Medicine, School of Health Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - J A Skinner
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia.,Faculty of Health and Medicine, School of Health Sciences, University of Newcastle, Callaghan, NSW, Australia
| | - M J Duncan
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW, Australia.,Faculty of Health and Medicine, School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, Australia
| |
Collapse
|
7
|
Owen AJ, Abramson MJ, Ikin JF, McCaffrey TA, Pomeroy S, Borg BM, Gao CX, Brown D, Liew D. Recommended Intake of Key Food Groups and Cardiovascular Risk Factors in Australian Older, Rural-Dwelling Adults. Nutrients 2020; 12:nu12030860. [PMID: 32210180 PMCID: PMC7146596 DOI: 10.3390/nu12030860] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 03/20/2020] [Accepted: 03/21/2020] [Indexed: 01/01/2023] Open
Abstract
This study examined the relationship between diet quality scores and cardiometabolic risk factors in regionally-dwelling older Australian adults with increased cardiovascular risk. This study was a cross-sectional analysis of demographic, anthropometric, and cardiometabolic risk factor data from 458 participants of the Cardiovascular Stream of the Hazelwood Health Study. Participants completed a 120 item semi-quantitative food frequency questionnaire. Multivariable linear regression adjusting for age, sex, smoking, physical activity, education, diabetes, and body mass index was used to examine the relationship between diet and cardiometabolic risk factors. Mean (SD) age of participants was 71 (8) years, and 55% were male. More than half of men and women did not meet recommended intakes of fibre, while 60% of men and 42% of women exceeded recommended dietary sodium intakes. Higher diet quality in terms of intake of vegetables, grains, and non-processed meat, as well as intake of non-fried fish, was associated with more favourable cardiometabolic risk profiles, while sugar-sweetened soft drink intake was strongly associated with adverse cardiometabolic risk factor levels. In older, regionally-dwelling adults, dietary public health strategies that address whole grain products, vegetable and fish consumption, and sugar-sweetened soft-drink intake may be of benefit in reducing cardiometabolic risk.
Collapse
Affiliation(s)
- Alice J. Owen
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
- Correspondence: ; Tel.: +61-3-9903-0045
| | - Michael J. Abramson
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| | - Jill F. Ikin
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| | - Tracy A. McCaffrey
- Department of Nutrition, Dietetics and Food, Monash University, Melbourne, VIC 3168, Australia;
| | - Sylvia Pomeroy
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| | - Brigitte M. Borg
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
- Respiratory Medicine, Alfred Hospital, Melbourne, VIC 3004, Australia
| | - Caroline X. Gao
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| | - David Brown
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| | - Danny Liew
- School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Rd, Melbourne, VIC 3004, Australia; (M.J.A.); (J.F.I.); (S.P.); (B.M.B.); (C.X.G.); (D.B.); (D.L.)
| |
Collapse
|
8
|
Baldwin JN, Forder PM, Haslam RL, Hure AJ, Loxton DJ, Patterson AJ, Collins CE. Change in Diet Quality over 12 Years in the 1946-1951 Cohort of the Australian Longitudinal Study on Women's Health. Nutrients 2020; 12:E147. [PMID: 31947981 PMCID: PMC7019671 DOI: 10.3390/nu12010147] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Revised: 12/17/2019] [Accepted: 01/02/2020] [Indexed: 12/18/2022] Open
Abstract
Understanding patterns of dietary change over time can provide important information regarding population nutrition behaviours. The aims were to investigate change in diet quality over 12 years in a nationally representative sample of women born in 1946-1951 and to identify characteristics of women whose diet quality changed over time. The Australian Recommended Food Score (ARFS) was measured in 2001 (n = 10,629, mean age 52.1 years) and 2013 (n = 9115; n = 8161 for both time points) for the mid-aged cohort from the Australian Longitudinal Study on Women's Health. Participants were categorised by tertiles of baseline diet quality and also classified as 'diet quality worsened' (ARFS decrease ≤ -4 points, n = 2361), 'remained stable' (-3 ≤ change in ARFS ≤ 3 points, n = 3077) or 'improved' (ARFS increase ≥ 4 points, n = 2723). On average, ARFS total and subscale scores remained relatively stable over time (mean [SD] change 0.3 [7.6] points) with some regression to the mean. Women whose diet quality worsened were more likely to be highly physically active at baseline compared with women whose diet quality improved (p < 0.001). Among women with poor diet quality initially (lowest baseline ARFS tertile, n = 2451, mean [SD] baseline ARFS 22.8 [4.5] points), almost half (47%, n = 1148) had not improved after 12 years, with women less likely to be in the healthy weight range (41% compared to 44%) and be never smokers (56% versus 62%, p < 0.05) compared with those whose diet improved. Diet quality remained relatively stable over 12 years' follow up among mid-aged women. Almost half of those with poor baseline diet quality remained poor over time, emphasizing the need to target high-risk groups for nutrition interventions.
Collapse
Affiliation(s)
- Jennifer N. Baldwin
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (R.L.H.); (A.J.P.)
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Peta M. Forder
- Research Centre for Generational Health & Ageing, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
| | - Rebecca L. Haslam
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (R.L.H.); (A.J.P.)
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia
| | - Alexis J. Hure
- Research Centre for Generational Health & Ageing, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW 2308, Australia
- Hunter Medical Research Institute, New Lambton Heights, NSW 2305, Australia
| | - Deborah J. Loxton
- Research Centre for Generational Health & Ageing, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
| | - Amanda J. Patterson
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (R.L.H.); (A.J.P.)
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia
- Research Centre for Generational Health & Ageing, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (P.M.F.); (A.J.H.); (D.J.L.)
| | - Clare E. Collins
- School of Health Sciences, Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW 2308, Australia; (J.N.B.); (R.L.H.); (A.J.P.)
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW 2308, Australia
| |
Collapse
|
9
|
Oftedal S, Holliday EG, Attia J, Brown WJ, Collins CE, Ewald B, Glozier N, McEvoy M, Morgan PJ, Plotnikoff RC, Stamatakis E, Vandelanotte C, Duncan MJ. Daily steps and diet, but not sleep, are related to mortality in older Australians. J Sci Med Sport 2019; 23:276-282. [PMID: 31615727 DOI: 10.1016/j.jsams.2019.09.018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 09/02/2019] [Accepted: 09/24/2019] [Indexed: 01/06/2023]
Abstract
OBJECTIVES Supporting healthy ageing is a key priority worldwide. Physical activity, diet quality and sleep are all associated with health outcomes, but few studies have explored their independent associations with all-cause mortality in an older population in the same model. The study aim was to examine associations between step-count, self-reported diet quality, restless sleep, and all-cause mortality in adults aged 55-85 years. DESIGN A prospective cohort study of adults in Newcastle, New South Wales, Australia. METHOD Data were from 1697 participants (49.3% women; baseline mean age 65.4 ± 7.1 years). Daily steps (measured by pedometer), diet quality (from a modified Australian Recommended Food Score), and frequency of restless sleep (by self-report) were assessed in relation to all-cause mortality using Cox proportional hazard regression with adjustment for sex, age, household income and smoking. Baseline data were collected between January 2005 and April 2008, and last follow-up was in March 2017 (median follow-up 9.6 years). RESULTS Higher step count (HR: 0.93, 95%CI: 0.88-0.98 per 1000-step increment) and higher diet quality (HR: 0.86, 95%CI: 0.74-0.99 per 8-point increment in diet quality score) were associated with reduced mortality risk. Restless sleep for ≥3 nights/week was not associated with mortality risk (HR: 1.03, 95%CI: 0.78-1.39). Sensitivity analyses, adjusting for chronic disease and excluding deaths <1 year after baseline, did not change these estimates. CONCLUSIONS Increased daily steps and consumption of a greater variety of nutrient-dense foods every week would result in substantial health benefits for older people. Future research should include a greater variety of sleep measures.
Collapse
Affiliation(s)
- Stina Oftedal
- School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, Australia; Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia.
| | | | - John Attia
- Centre for Clinical Epidemiology and Biostatistics, Hunter Medical Research Institute and School of Medicine and Public Health, University of Newcastle, Australia
| | - Wendy J Brown
- School of Human Movement and Nutrition Sciences, The University of Queensland, Australia
| | - Clare E Collins
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia
| | - Benjamin Ewald
- Centre for Clinical Epidemiology and Biostatistics, The University of Newcastle, Australia
| | - Nicholas Glozier
- Brain and Mind Centre, Central Clinical School, The University of Sydney, Australia
| | - Mark McEvoy
- Centre for Clinical Epidemiology and Biostatistics, The University of Newcastle, Australia; Hunter Medical Research Institute, Australia
| | - Philip J Morgan
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia; School of Education, Faculty of Education and Arts, The University of Newcastle, Australia
| | - Ronald C Plotnikoff
- Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia
| | - Emmanuel Stamatakis
- Charles Perkins Centre, The University of Sydney, Australia; Prevention Research Collaboration, School of Public Health, The University of Sydney, Australia
| | - Corneel Vandelanotte
- Physical Activity Research Group, Appleton Institute, Central Queensland University, Australia
| | - Mitch J Duncan
- School of Medicine & Public Health, Faculty of Health and Medicine, The University of Newcastle, Australia; Priority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Australia
| |
Collapse
|
10
|
|
11
|
Harbury C, Collins CE, Callister R. Diet quality is lower among adults with a BMI ≥40kgm -2 or a history of weight loss surgery. Obes Res Clin Pract 2018; 13:197-204. [PMID: 30409499 DOI: 10.1016/j.orcp.2018.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 07/20/2018] [Accepted: 10/22/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND Poor diet is a major public health issue requiring strategies to support improvements. Nutrition knowledge influences eating behaviours, yet few studies have examined relationships with diet quality. The current study aimed to explore relationships between demographic characteristics, nutrition knowledge, and diet quality using the Australian Recommended Food Score (measuring diet variety). METHODS Adults 18-60 years completed a 210-item survey including questions on demographics, health, nutrition knowledge, and diet. Statistical analysis used chi-square tests, linear and multiple regression, adjusted for covariates. RESULTS 480 respondents with a mean (SD) age 39.1±11.6 years (18% male) completed all questions. Overall diet quality scores were high (ARFS 39.5±9 points). Nutrition knowledge (p<0.001) and BMI (p<0.001) were positively associated with ARFS. ARFS scores were higher for those with higher nutrition knowledge scores (ARFS 42±8 points) and of lower BMI (ARFS 40±8 points) compared to those with lower knowledge (ARFS 37±11) and higher BMI (ARFS 35±10 points). Those with BMI≥40kg·m-2 and weight loss surgery reported the lowest diet quality (ARFS 31±10 points). CONCLUSION Diet quality was highest among those with high nutrition knowledge and lower BMI. Those with a BMI ≥40kg·m-2, particularly those with past weight loss surgery reported the lowest diet quality, despite comparable levels of nutrition knowledge. It remains unclear which factors explain the variation in diet quality in the weight loss surgery group and this deserves further attention given the growing popularity of weight loss surgery.
Collapse
Affiliation(s)
- Cathy Harbury
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW Australia.
| | - Clare E Collins
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW Australia
| | - Robin Callister
- Priority Research Centre for Physical Activity and Nutrition, University of Newcastle, Callaghan, NSW Australia; Faculty of Health and Medicine, School of Biomedical Sciences and Pharmacy, University of Newcastle, Callaghan, NSW, Australia
| |
Collapse
|