As part of the 12-month follow-up of the longitudinal cohort study, Life and Living in Advanced Age: A Cohort Study in New Zealand, dietary intake was assessed in 216 Māori and 362 non-Māori octogenarians using repeat 24-h multiple pass recalls. Energy and macronutrient intakes were calculated, and food items reported were allocated to food groups used in the New Zealand Adult Nutrition Survey (NZANS). Intakes were compared with the nutrient reference values (NRV) for Australia and New Zealand. The median BMI was higher for Māori (28·3 kg/m2) than for non-Māori (26·2 kg/m2) P=0·007. For Māori, median energy intake was 7·44 MJ/d for men and 6·06 MJ/d for women with 16·3 % energy derived from protein, 43·3 % from carbohydrate and 38·5 % from fat. Median energy intake was 7·91 and 6·26 MJ/d for non-Māori men and women, respectively, with 15·4 % of energy derived from protein, 45 % from carbohydrate and 36·7 % from fat. For both ethnic groups, bread was the top contributor to energy and carbohydrate intakes. Protein came from beef and veal, fish and seafood, bread, milk and poultry with the order differing by ethnic groups and sex. Fat came mainly from butter and margarine. Energy-adjusted protein was higher for Māori than non-Māori (P=0·049). For both ethnic groups, the median energy levels were similar, percent carbohydrate tended to be lower and percent fat higher compared with adults aged >70 years in NZANS. These unique cross-sectional data address an important gap in our understanding of dietary intake in this growing section of our population and highlight lack of age-appropriate NRV.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1017/S0007114516003020 | DOI Listing |
J Med Internet Res
January 2025
Hospital Administration, Ramaiah Memorial Hospital, Bengaluru, Karnataka, India.
Background: Monitoring vital signs in hospitalized patients is crucial for evaluating their clinical condition. While early warning scores like the modified early warning score (MEWS) are typically calculated 3 to 4 times daily through spot checks, they might not promptly identify early deterioration. Leveraging technologies that provide continuous monitoring of vital signs, combined with an early warning system, has the potential to identify clinical deterioration sooner.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Institute of Nursing Science, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
Background: Health care systems and the nursing profession worldwide are being transformed by technology and digitalization. Nurses acquire digital competence through their own experience in daily practice, but also from education and training; nursing education providers thus play an important role. While nursing education providers have some level of digital competence, there is a need for ongoing training and support for them to develop more advanced skills and effectively integrate technology into their teaching.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Indiana University, Indianapolis, IN, United States.
Background: Heart failure (HF) is one of the most common causes of hospital readmission in the United States. These hospitalizations are often driven by insufficient self-care. Commercial mobile health (mHealth) technologies, such as consumer-grade apps and wearable devices, offer opportunities for improving HF self-care, but their efficacy remains largely underexplored.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Commonwealth Scientific and Industrial Research Organisation, Adelaide, Australia.
Background: A greater understanding of the effectiveness of digital self-management programs and their ability to support longer-term weight loss is needed.
Objective: This study aimed to explore the total weight loss and patterns of weight loss of CSIRO (Commonwealth Scientific and Industrial Research Organisation) Total Wellbeing Diet Online members during their first 12 months of membership and examine the patterns of platform use associated with greater weight loss.
Methods: Participants were Australian adults who joined the program between October 2014 and June 2022 and were classified as longer-term members, meaning they completed at least 12 weeks of the program, had baseline and 12-week weight data, and had a paid membership of ≥1 year (N=24,035).
J Med Internet Res
January 2025
School of Public Health, Capital Medical University, Beijing, China.
Background: Health inequalities among older adults become increasingly pronounced as aging progresses. In the digital era, some researchers argue that access to and use of digital technologies may contribute to or exacerbate these existing health inequalities. Conversely, other researchers believe that digital technologies can help mitigate these disparities.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!