Comparison of multiple and novel measures of dietary glycemic carbohydrate with insulin resistant status in older women

BACKGROUND:Previous epidemiological investigations of associations between dietary glycemic intake and insulin resistance have used average daily measures of glycemic index (GI) and glycemic load (GL). We explored multiple and novel measures of dietary glycemic intake to determine which was most predictive of an association with insulin resistance.METHODS:Usual dietary intakes were assessed by diet history interview in women aged 42-81 years participating in the Longitudinal Assessment of Ageing in Women. Daily measures of dietary glycemic intake (n = 329) were carbohydrate, GI, GL, and GL per megacalorie (GL/Mcal), while meal based measures (n = 200) were breakfast, lunch and dinner GL; and a new measure, GL peak score, to represent meal peaks. Insulin resistant status was defined as a homeostasis model assessment (HOMA) value of >3.99; HOMA as a continuous variable was also investigated.RESULTS:GL, GL/Mcal, carbohydrate (all P < 0.01), GL peak score (P = 0.04) and lunch GL (P = 0.04) were positively and independently associated with insulin resistant status. Daily measures were more predictive than meal-based measures, with minimal difference between GL/Mcal, GL and carbohydrate. No significant associations were observed with HOMA as a continuous variable.CONCLUSION:A dietary pattern with high peaks of GL above the individual's average intake was a significant independent predictor of insulin resistance in this population, however the contribution was less than daily GL and carbohydrate variables. Accounting for energy intake slightly increased the predictive ability of GL, which is potentially important when examining disease risk in more diverse populations with wider variations in energy requirements

Maternal work hours in early to middle childhood link to later adolescent diet quality

Objective: Previous studies on maternal work hours and child diet quality have reported conflicting findings possibly due to differences in study design, lack of a comprehensive measure of diet quality and differing ages of the children under investigation. The present study aimed to prospectively examine the impact of parental work hours from age 1 year to age 14 years on adolescent diet quality. Design: Multivariate linear regression models were used to examine independent associations between parents’ work hours at each follow-up and across 14 years and adolescent diet quality at age 14 years. A diet quality index was based on the international literature and Australian recommendations, consisting of six food groups and nine nutrients. Setting: Perth, Western Australia. Subjects: Children (n 1629) participating in the Western Australian Pregnancy Cohort (Raine) Study. Results: Compared with children of mothers in full-time employment, children of mothers who were not employed in early childhood up to age 5 years had a higher average diet quality score at age 14 years, independent of maternal and family socio-economic status. Across 14 years the number of years the mother worked full time and increasing average weekly hours were associated with lower diet quality. Father’s work hours had little association with adolescent diet quality. Conclusions: Having a mother stay at home in early to middle childhood is associated with better diet quality in adolescence. Support may be beneficial for families where the mother returns to full-time employment before the child reaches 8 years of age

Seeing lockdown through the eyes of children from around the world: Reflecting on a children's artwork project.

The COVID-19 pandemic created new challenges for children including access to education and limiting social and emotional connections to extended family, friends, and the community. Globally, opportunities for sharing children’s self-reported experiences during lockdown were limited. The primary aim of this project was to create an art-E-Book that reflects children’s experiences of life during the COVID-19 pandemic that could be shared with other children around the world. Secondly, we wanted to reflect on the consultation undertaken within the International Network of Child and Family Centered Care (INCFCC) using Gibbs (1988) reflective cycle framework. Children from around the world were invited to submit a piece of artwork that reflected their experience during the COVID-19 pandemic via a Qualtrics-survey in May 2020. The children’s artwork and written pieces were transcribed verbatim into an E-Book and the artwork was further placed into groups based on similarity of meaning. Fifty-five children from 17 countries submitted an artwork piece. Four groups were evident within the children’s artwork including infection control measures, positive experiences and emotions (connection to family, fun activities), negative experiences and emotions (social impact, emotional impact), and uniting children globally. The E-Book is available to download free of charge via the INCFCC website. The E-Book illustrates how children of all ages can provide meaningful insightful commentary and valuable information on their experiences during an unprecedented pandemic

Genome sequencing with gene panel-based analysis for rare inherited conditions in a publicly funded healthcare system: implications for future testing

Acknowledgements This study would not be possible without the families, patients, clinicians, nurses, research scientists, laboratory staff, informaticians and the wider Scottish Genomes Partnership team to whom we give grateful thanks. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project. The 100,000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health). The Scottish Genomes Partnership was funded by the Chief Scientist Office of the Scottish Government Health Directorates (SGP/1) and The Medical Research Council Whole Genome Sequencing for Health and Wealth Initiative (MC/PC/15080). The 100,000 Genomes Project is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK and the Medical Research Council have also funded research infrastructure.Peer reviewedPublisher PD

The relationship between glycemic intake and insulin resistance in older women

Glycemic intake influences the rise in blood glucose concentration following consumption of a carbohydrate containing meal, known as the postprandial glycemic response. The glycemic response is a result of both the type and amount of carbohydrate foods consumed and is commonly measured as the glycemic index (GI) or glycemic load (GL), where the GI is a ranking in comparison to glucose and the GL is an absolute value encompassing both the GI and amount of carbohydrate consumed. Evidence from controlled trials in rat models suggests that glycemic intake has a role in development of insulin resistance, however trials and observational studies of humans have produced conflicting results. As insulin resistance is a precursor to type 2 diabetes mellitus, lifestyle factors that could prevent development of this condition have important public health implications. Previous observational studies have used food frequency questionnaires to assess usual diet, which could have resulted in a lack of precision in assessment of individual serve sizes, and have been limited to daily measures of glycemic intake. Daily measures do not take fluctuations in glycemic intake on a per meal basis into account, which may be a more relevant measure for investigation in relation to disease outcomes. This PhD research was conducted in a group of Brisbane women aged 42 to 81 years participating in the multidisciplinary Brisbane Longitudinal Assessment of Ageing in Women (LAW study). Older women may be at particular risk of insulin resistance due to age, hormonal changes, and increases in abdominal obesity associated with menopause, and the LAW study provided an ideal opportunity to study the relationship between diet and insulin resistance. Using the diet history tool, we aimed to assess the glycemic intake of the population and hypothesised that daily GI and daily GL would be significantly positively associated with increased odds of insulin resistant status. We also hypothesised that a new glycemic measure representing peaks in GL at different meals would be a stronger predictor of insulin resistant status than daily measures, and that a specially designed questionnaire would be an accurate and repeatable dietary tool for assessment of glycemic intake. To address these hypotheses, we conducted a series of studies. To assess glycemic intake, information on usual diet was obtained by detailed diet history interview and analysed using Foodworks and the Australian Food and Nutrient (AUSNUT) database, combined with a customised GI database. Mean ± SD intakes were 55.6 ± 4.4% for daily GI and 115 ± 25 for daily GL (n=470), with intake higher amoung younger participants. Bread was the largest contributor to intakes of daily GI and GL (17.1% and 20.8%, respectively), followed by fruit (15.5% and 14.2%, respectively). To determine whether daily GI and GL were significantly associated with insulin resistance, the homeostasis model assessment of insulin resistance (HOMA) was used to assess insulin resistant status. Daily GL was significantly higher in subjects who were insulin resistant compared to those who were not (134 ± 33 versus 114 ± 24 respectively, P<0.001) (n=329); the odds of subjects in the highest tertile of GL intake being insulin resistant were 12.7 times higher when compared with the lowest tertile of GL (95% CI 1.6-100.1, P=0.02). Daily GI was not significantly different in subjects who were insulin resistant compared to those who were not (56.0 ± 3.3% versus 55.7 ± 4.5%, P=0.69). To evaluate whether a new glycemic measure representing fluctuations in daily glycemic intake would be a stronger predictor of insulin resistant status than other glycemic intake measures, the GL peak score was developed to express in a single value the magnitude of GL peaks during an average day. Although a significant relationship was seen between insulin resistant status and GL peak score (Nagelkerke’s R2=0.568, P=0.039), other glycemic intake measures of daily GL (R2=0.671, P<0.001) and daily GL per megajoule (R2=0.674, P<0.001) were stronger predictors of insulin resistant status. To develop an accurate and repeatable self-administered tool for assessment of glycemic intake, two sub-samples of women (n=44 for the validation study and n=52 for the reproducibility study) completed a semi-quantitative questionnaire that contained 23 food groupings selected to include the top 100 carbohydrate foods consumed by the study population. While there were significant correlations between the glycemic intake questionnaire and the diet history for GL (r=0.54, P<0.01), carbohydrate (r=0.57, P<0.01) and GI (r=0.40, P<0.01), Bland-Altman plots showed an unacceptable difference between individual intakes in 34% of subjects for daily GL and carbohydrate, and 41% for daily GI. Reproducibility results showed significant correlations for daily GL (r=0.73, P<0.001), carbohydrate (r=0.76, P<0.001) and daily GI (r=0.64, P<0.001), but an unacceptable difference between individual intakes in 25% of subjects for daily GL and carbohydrate, and 27% for daily GI. In summary, our findings show that a significant association was observed between daily glycemic load and insulin resistant status in a group of older women, using a diet history interview to obtain precise estimation of individual carbohydrate intake. Both the type and quantity of carbohydrate are important to consider when investigating relationships between diet and insulin resistance, although our results suggest the association is more closely related to overall daily glycemic intake than individual meal intake variations. A dietary tool that permits precise estimation of carbohydrate intake is essential when evaluating possible associations between glycemic intake and individual risk of chronic diseases such as insulin resistance. Our results also suggest that studies using questionnaires to estimate glycemic intake should state degree of agreement as well as correlation coefficients when evaluating validity, as imprecise estimates of carbohydrate at an individual level may have contributed to the conflicting findings reported in previous studies

The relationship between glycemic intake and insulin resistance in older women

Glycemic intake influences the rise in blood glucose concentration following consumption of a carbohydrate containing meal, known as the postprandial glycemic response. The glycemic response is a result of both the type and amount of carbohydrate foods consumed and is commonly measured as the glycemic index (GI) or glycemic load (GL), where the GI is a ranking in comparison to glucose and the GL is an absolute value encompassing both the GI and amount of carbohydrate consumed. Evidence from controlled trials in rat models suggests that glycemic intake has a role in development of insulin resistance, however trials and observational studies of humans have produced conflicting results. As insulin resistance is a precursor to type 2 diabetes mellitus, lifestyle factors that could prevent development of this condition have important public health implications. Previous observational studies have used food frequency questionnaires to assess usual diet, which could have resulted in a lack of precision in assessment of individual serve sizes, and have been limited to daily measures of glycemic intake. Daily measures do not take fluctuations in glycemic intake on a per meal basis into account, which may be a more relevant measure for investigation in relation to disease outcomes. This PhD research was conducted in a group of Brisbane women aged 42 to 81 years participating in the multidisciplinary Brisbane Longitudinal Assessment of Ageing in Women (LAW study). Older women may be at particular risk of insulin resistance due to age, hormonal changes, and increases in abdominal obesity associated with menopause, and the LAW study provided an ideal opportunity to study the relationship between diet and insulin resistance. Using the diet history tool, we aimed to assess the glycemic intake of the population and hypothesised that daily GI and daily GL would be significantly positively associated with increased odds of insulin resistant status. We also hypothesised that a new glycemic measure representing peaks in GL at different meals would be a stronger predictor of insulin resistant status than daily measures, and that a specially designed questionnaire would be an accurate and repeatable dietary tool for assessment of glycemic intake. To address these hypotheses, we conducted a series of studies. To assess glycemic intake, information on usual diet was obtained by detailed diet history interview and analysed using Foodworks and the Australian Food and Nutrient (AUSNUT) database, combined with a customised GI database. Mean ± SD intakes were 55.6 ± 4.4% for daily GI and 115 ± 25 for daily GL (n=470), with intake higher amoung younger participants. Bread was the largest contributor to intakes of daily GI and GL (17.1% and 20.8%, respectively), followed by fruit (15.5% and 14.2%, respectively). To determine whether daily GI and GL were significantly associated with insulin resistance, the homeostasis model assessment of insulin resistance (HOMA) was used to assess insulin resistant status. Daily GL was significantly higher in subjects who were insulin resistant compared to those who were not (134 ± 33 versus 114 ± 24 respectively, P<0.001) (n=329); the odds of subjects in the highest tertile of GL intake being insulin resistant were 12.7 times higher when compared with the lowest tertile of GL (95% CI 1.6-100.1, P=0.02). Daily GI was not significantly different in subjects who were insulin resistant compared to those who were not (56.0 ± 3.3% versus 55.7 ± 4.5%, P=0.69). To evaluate whether a new glycemic measure representing fluctuations in daily glycemic intake would be a stronger predictor of insulin resistant status than other glycemic intake measures, the GL peak score was developed to express in a single value the magnitude of GL peaks during an average day. Although a significant relationship was seen between insulin resistant status and GL peak score (Nagelkerke’s R2=0.568, P=0.039), other glycemic intake measures of daily GL (R2=0.671, P<0.001) and daily GL per megajoule (R2=0.674, P<0.001) were stronger predictors of insulin resistant status. To develop an accurate and repeatable self-administered tool for assessment of glycemic intake, two sub-samples of women (n=44 for the validation study and n=52 for the reproducibility study) completed a semi-quantitative questionnaire that contained 23 food groupings selected to include the top 100 carbohydrate foods consumed by the study population. While there were significant correlations between the glycemic intake questionnaire and the diet history for GL (r=0.54, P<0.01), carbohydrate (r=0.57, P<0.01) and GI (r=0.40, P<0.01), Bland-Altman plots showed an unacceptable difference between individual intakes in 34% of subjects for daily GL and carbohydrate, and 41% for daily GI. Reproducibility results showed significant correlations for daily GL (r=0.73, P<0.001), carbohydrate (r=0.76, P<0.001) and daily GI (r=0.64, P<0.001), but an unacceptable difference between individual intakes in 25% of subjects for daily GL and carbohydrate, and 27% for daily GI. In summary, our findings show that a significant association was observed between daily glycemic load and insulin resistant status in a group of older women, using a diet history interview to obtain precise estimation of individual carbohydrate intake. Both the type and quantity of carbohydrate are important to consider when investigating relationships between diet and insulin resistance, although our results suggest the association is more closely related to overall daily glycemic intake than individual meal intake variations. A dietary tool that permits precise estimation of carbohydrate intake is essential when evaluating possible associations between glycemic intake and individual risk of chronic diseases such as insulin resistance. Our results also suggest that studies using questionnaires to estimate glycemic intake should state degree of agreement as well as correlation coefficients when evaluating validity, as imprecise estimates of carbohydrate at an individual level may have contributed to the conflicting findings reported in previous studies

Memory Loss in the Early Stages of Alzheimer's Disease

The purpose of the study was to examine any semantic memory deficit in the early stages of Alzheimer's disease (AD) and further define the nature of any deficit found. In experiment one, 30 participants with AD and 30 age, gender and education-matched control participants completed a series of semantic memory tasks, an independent test of frontal lobe functioning (tower of Hanoi), a global screening measure, and measures of anxiety and depression. Participants with AD were in the early stages of the disease and divided into minimal and mild subgroups. In addition a further amnesic subgroup showed relatively intact global scores alongside impaired semantic memory task performance. Significant between-group effects were observed across the range of semantic memory tasks. In addition, dissociations were found between tower of Hanoi performance and performance on semantic memory tasks. These findings lend support to the view that semantic memory difficulties are due to underlying damage to the structure of semantic memory, rather than resulting from an access or organisational problem. The performance of the amnesic group raises the possibility that semantic memory loss may represent a preclinical stage of the disease process in AD.In experiment two, eight participants with probable AD and eight age, gender and educationmatched control participants took part. The effects of imageability and age of acquisition (AoA) were examined along with attribute knowledge of animals and objects. Results showed that imageability made a strong contribution to semantic associations while the effect of AoA was small, but significant. Imageability, thought to produce stronger activation, may assist in recall of semantic memory items, while the somewhat meagre AoA effect raises questions concerning the temporal gradient of memory loss thought to occur in AD. Attribute knowledge was characterised by loss of subordinate knowledge alongside naming ability which was only minimally affected. Overall results suggest a loss of associations in semantic memory in the early stages of AD, along with a loss of subordinate knowledge and a strengthening of easily accessed responses. No differences were found between living and nonliving items, however knowledge of functional use of objects appeared comparatively well preserved.</p