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Background: The New Zealand (NZ) Ministry of Health ethnicity data protocols recommend that people of South Asian (SAsian) ethnicity, other than Indian, are combined with people of Japanese and Korean ethnicity at the most commonly used level of aggregation in health research (level two). This may not work well for perinatal studies, as it has long been observed that women of Indian ethnicity have higher rates of adverse pregnancy outcomes, such as perinatal death. It is possible that women of other SAsian ethnicities share this risk. Aims: This study was performed to identify appropriate groupings of women of SAsian ethnicity for perinatal research. Materials and Methods: National maternity and neonatal data, and singleton birth records between 2008 and 2017 were linked using the Statistics NZ Integrated Data Infrastructure. Socio‐demographic risk profiles and pregnancy outcomes were compared between 15 ethnic groups. Recommendations were made based on statistical analyses and cultural evaluation with members of the SAsian research community. Results: Similarities were observed between women of Indian, Fijian Indian, South African Indian, Sri Lankan, Bangladeshi and Pakistani ethnicities. A lower‐risk profile was seen among Japanese and Korean mothers. Risk profiles of women of combined Indian‐Māori, Indian‐Pacific and Indian‐New Zealand European ethnicity more closely represented their corresponding non‐Indian ethnicities. Conclusions: Based on these findings, we suggest a review of current NZ Ministry of Health ethnicity data protocols. We recommend that researchers understand the risk profiles of participants prior to aggregation of groups in research, to mitigate risks associated with masking differences. [ABSTRACT FROM AUTHOR]

Aim: Total gastrectomy and Ivor Lewis oesophagectomy procedures are the mainstay of upper gastrointestinal cancer management. Maintenance of adequate nutritional intake is essential for positive patient outcomes. Although numerous nutritional support options exist, clear evidence‐based guidelines on the optimal means and duration of nutritional support are lacking. The aim of this study is to establish preliminary data on the current perioperative nutritional practices of upper gastrointestinal surgeons performing these procedures across Australia and New Zealand. It is hoped this will help provide the platform for future research towards establishing evidence‐based guidelines in upper gastrointestinal surgery. Methods: A questionnaire exploring the nutritional practices and considerations of surgeons was developed and emailed to the members of the Australia & New Zealand Gastric & Oesophageal Surgery Association. Results: A total of 27.4% of Australia & New Zealand Gastric & Oesophageal Surgery Association members completed the questionnaire. Surgeons reported inserting a jejunostomy feeding tube intraoperatively in Ivor Lewis oesophagectomy procedures 80–100% of the time, compared to only 20–39% of the time in total gastrectomy procedures. For both procedures, surgeons often refer their patients to a dietitian preoperatively, and always postoperatively. Preoperative immune‐enhancing nutrition is rarely administered. Patient age and BMI are deemed to be of low importance when determining the means of nutritional support. Conclusions: This study has demonstrated the current nutritional practices employed in Australia and New Zealand for patients undergoing major upper gastrointestinal surgery. Questions remain regarding the noted differences between procedures as well as the optimal means and duration of perioperative nutritional support. [ABSTRACT FROM AUTHOR]

Aim: To establish the prevalence of nutrition risk and associated risk factors among adults of advanced age newly admitted to hospital. Methods: A cross‐sectional study was undertaken in adults aged over 85 years admitted to one of two hospital wards in Auckland within the previous 5 days. An interviewer‐administered questionnaire was used to establish participant's socio‐demographic and health characteristics. Markers of body composition and muscle strength were collected. Nutrition risk was assessed using the Mini Nutritional Assessment‐Short Form (MNA‐SF), dysphagia risk using the 10‐Item Eating Assessment Tool (EAT‐10) and level of cognition using the Montreal Cognitive Assessment. Results: A total of 88 participants with a mean age of 90.0 ± 3.7 years completed the assessments. A third (28.4%) of the participants were categorised by the MNA‐SF as malnourished and 43.2% were classified at risk of malnutrition. A third (29.5%) were at risk of dysphagia as assessed by EAT‐10. Malnourished participants were more likely to be at risk of dysphagia (P = 0.015). The MNA‐SF score was positively correlated with body mass index (r = 0.484, P < 0.001) and grip strength (r = 0.250, P = 0.026) and negatively correlated with risk of dysphagia (r = −0.383, P < 0.001). Conclusions: Among newly hospitalised adults of advanced age, over two thirds were malnourished or at risk of malnutrition, and a third were at risk of dysphagia. Nutrition risk was positively correlated with low BMI and grip strength and negatively correlated with dysphagia risk. Findings highlight the importance of screening for dysphagia risk, especially in those identified to be malnourished or at nutrition risk. [ABSTRACT FROM AUTHOR]

Objective To derive novel emergency weight estimation tables for New Zealand children aged 5-10 years using ethnicity and sex to increase accuracy and precision. Methods Using an existing dataset (collected in five New Zealand primary schools during July 2013; n = 376), body mass index and current emergency weight estimates were calculated. Stepwise regression with Akanke Information produced two best-fit models for predicting weight, one based on age and the other on height. Potential explanatory variables included ethnicity, sex and body habitus. Results The length-based model included height, ethnicity and body habitus. Accuracy (weight estimates within 10% of actual weight) for the length-based lookup table (74.8%) was similar to that for the Broselow-Luten tape (73.4%). The age-based model included age, sex, ethnicity and body habitus. Accuracy (51.3%) for the age-based lookup table was better than for existing formulae including Shann (45.7%), Advanced Paediatric Life Support (39.1%) and Theron (28.7%). Conclusion The most accurate method for weight estimation in Auckland children aged 5-10 years is either the novel length-based lookup table or the existing Broselow-Luten tape. When length-based methods are not possible, the age-based lookup tables incorporating age, sex, ethnicity and body habitus are more accurate than existing methods of weight estimation. [ABSTRACT FROM AUTHOR]

Purpose: To measure the iodine status and iodine intake of New Zealand adults 18-64 years of age following mandatory fortification of bread with iodine. Methods: A cross-sectional survey of NZ adults living in Dunedin and Wellington during February-November 2012. Three hundred and one men and women aged 18-64 years randomly selected from the New Zealand Electoral Roll completed a 24-h urine collection, a demographic and iodine-specific food frequency questionnaire (FFQ), and had height and weight measured. Urine collections were analysed for iodine and reported as median urinary iodine concentration (UIC) µg/L and median urinary iodine excretion (UIE) µg/day. The FFQ was used to estimate iodine intake with and without discretionary iodised salt use. Results: The median UIC for all adults was 73 µg/L, indicative of mild iodine deficiency. The mean urinary volume was 2.0 L. As an estimate of iodine intake, the median UIE was 127 µg/day. Estimated iodine intake, using the FFQ which included discretionary iodised salt use, was 132 µg/day. Iodine intakes were associated with UIC ( P = 0.040) and UIE ( P = 0.003), but not with bread iodine intake and iodised salt use. Conclusion: Using the WHO/UNICEF/ICCIDD target for iodine sufficiency (a UIC of >100 µg/L) based on school-aged children with a mean urinary volume of 1.0 L, the iodine status of NZ adults does not reach adequate levels (73 µg/L). A more realistic parameter in a population with a higher urinary volume excretion (2.0 L) is the UIE. A median UIE of 127 µg/day suggests that the iodine status of NZ adults is now likely to be adequate. [ABSTRACT FROM AUTHOR]

ABSTRACT BACKGROUND The aim of this study was to determine the association between the school nutrition climate and students' eating behaviors and body mass index (BMI). METHODS Data were collected as part of Youth'07, a nationally representative health survey of high school students in New Zealand. Overall, 9107 randomly selected students from 96 randomly selected schools participated. School-level measures were created by aggregating students' reports within schools. Analyses were conducted using multilevel modeling, accounting for student-level characteristics. RESULTS There was a positive association between the school nutrition climate and students' consumption of fruits and vegetables. This relationship was statistically significant after controlling for the background characteristics of students. There were no associations between the school nutrition climate and students' junk food consumption or BMI. CONCLUSIONS The school nutrition climate appears to have a positive influence on adolescents' healthy eating behaviors (fruit and vegetable intake), but a limited effect on unhealthy eating behaviors and ultimately body weight. This may reflect the pervasiveness of junk food in the environments of adolescents outside of school and the difficulty in limiting its consumption. [ABSTRACT FROM AUTHOR]

The aim of the study was to validate the self-report Multimedia Activity Recall for Children and Adolescents (MARCA) against accelerometry for the assessment of physical activity in New Zealand children. Participants (n = 716, 10–18 years) recalled 3–4 days of activity using the MARCA and underwent a partially overlapping 7-day accelerometry protocol during a national survey. Spearman correlation coefficients (ρ) assessed the association between accelerometer-derived counts per minute and MARCA-derived physical activity level and time in locomotion. Both data sources estimated time spent in light and moderate–vigorous physical activity. Association and agreement between methods for light physical activity and moderate–vigorous physical activity was assessed using correlations and Bland–Altman plots respectively, and pairedt-tests conducted. Accelerometer-derived activity counts were moderately correlated with both MARCA-derived physical activity level and locomotion (ρ = 0.38,P < 0.0001). The correlation between methods was –0.14 for light physical activity and 0.28 for moderate–vigorous physical activity (P < 0.0001). The MARCA overestimated moderate–vigorous physical activity compared with accelerometry (120 min,P < 0.0001), which increased as moderate–vigorous physical activity time increased. Some sex and ethnicity (Māori [indigenous] versus non-Māori) differences were observed. Overall, the MARCA indicated moderate validity for assessment of physical activity level, locomotion and moderate–vigorous physical activity and poor validity for assessment of light physical activity. This was comparable to other self-report tools. The MARCA has utility for future large-scale research. [ABSTRACT FROM PUBLISHER]

Summary: Background: There is a relationship between childhood obesity and area‐level deprivation. While the New Zealand Index of Deprivation (NZDep) has been used widely in research for the past 20 years, the Index of Multiple Deprivation (IMD) was released in 2017. This study aims to investigate the association between deprivation and childhood obesity in New Zealand and compare measures of deprivation. Methods: Data from 316 794 4‐year‐olds in New Zealand undertaking the B4 School Check in 2010 to 2016, a national health and development screen, were analysed. Multilevel logistic regression models assessed the relationship between area‐level deprivation and individual‐level child obesity. Models were adjusted for age, sex, immigration status, ethnicity, and year. Deprivation was measured using the census‐based NZDep2013 (deciles) and the administrative data‐based IMD (deciles). The seven domains of the IMD were also considered. Results: The relationship between deprivation and obesity was very similar for the IMD and NZDep2013, point estimates were near identical, and confidence intervals overlapped substantially. Higher levels of deprivation were associated with a higher prevalence of child obesity. The relationship between deprivation and child obesity varied considerably across IMD domains. The education domain had the strongest association with child obesity and had an association with child obesity independent of the other domains of deprivation. Conclusion: Overall, there was little difference between the NZDep and IMD. However, the IMD's domains and IMD‐1 approach reveal more nuanced understandings of the deprivation‐obesity gradient, including the importance of area‐level education deprivation for predicting child obesity rates. [ABSTRACT FROM AUTHOR]