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Background: Significant progress has been made addressing adolescent health needs in New Zealand, but some areas, such as mental health issues remain, particularly for rangatahi Māori (indigenous Māori young people). Little is known about how contemporary Māori whānau (families) and communities influence health outcomes, health literacy and access to services. Previous nationally representative secondary school surveys were conducted in New Zealand in 2001, 2007 and 2012, as part of the Youth2000 survey series. This paper focuses on a fourth survey conducted in 2019 (https://www.youth19.ac.nz/). In 2019, the survey also included kura kaupapa Māori schools (Māori language immersion schools), and questions exploring the role of family connections in health and wellbeing. This paper presents the overall study methodology, and a weighting and calibration framework in order to provide estimates that reflect the national student population, and enable comparisons with the previous surveys to monitor trends. Methods: Youth19 was a cross sectional, self-administered health and wellbeing survey of New Zealand high school students. The target population was the adolescent population of New Zealand (school years 9–13). The study population was drawn from three education regions: Auckland, Tai Tokerau (Northland) and Waikato. These are the most ethnically diverse regions in New Zealand. The sampling design was two-stage clustered stratified, where schools were the clusters, and strata were defined by kura schools and educational regions. There were four strata, formed as follows: kura schools (Tai Tokerau, Auckland and Waikato regions combined), mainstream-Auckland, mainstream-Tai Tokerau and mainstream-Waikato. From each stratum, 50% of the schools were randomly sampled and then 30% of students from the selected schools were invited to participate. All students in the kura kaupapa schools were invited to participate. In order to make more precise estimates and adjust for differential non-response, as well as to make nationally relevant estimates and allow comparisons with the previous national surveys, we calibrated the sampling weights to reflect the national secondary school student population. Results: There were 45 mainstream and 4 kura schools included in the final sample, and 7,374 mainstream and 347 kura students participated in the survey. There were differences between the sampled population and the national secondary school student population, particularly in terms of sex and ethnicity, with a higher proportion of females and Asian students in the study sample than in the national student population. We calculated estimates of the totals and proportions for key variables that describe risk and protective factors or health and wellbeing factors. Rates of risk-taking behaviours were lower in the sampled population than what would be expected nationally, based on the demographic profile of the national student population. For the regional estimates, calibrated weights yield standard errors lower than those obtained with the unadjusted sampling weights. This leads to significantly narrower confidence intervals for all the variables in the analysis. The calibrated estimates of national quantities provide similar results. Additionally, the national estimates for 2019 serve as a tool to compare to previous surveys, where the sampling population was national. Conclusions: One of the main goals of this paper is to improve the estimates at the regional level using calibrated weights to adjust for oversampling of some groups, or non-response bias. Additionally, we also recommend the use of calibrated estimators as they provide nationally adjusted estimates, which allow inferences about the whole adolescent population of New Zealand. They also yield confidence intervals that are significantly narrower than those obtained using the original sampling weights. [ABSTRACT FROM AUTHOR]

Weeds are increasingly documented with evolved resistance to herbicides globally. Three species have been reported as resistant in maize crops in New Zealand: Chenopodium album to atrazine and dicamba, Persicaria maculosa to atrazine and Digitaria sanguinalis to nicosulfuron. Despite knowledge of these cases, the distribution of these resistant biotypes is unknown. This study aimed to determine the prevalence of known resistant weeds in major maize growing areas in New Zealand, and to pro-actively screen other species for resistance. Weed seeds of broadleaf and grass species were collected from 70 randomly selected maize growing farms in the North Island in 2021–2022. Seeds were grown and treated with herbicides at recommended field rates. Atrazine-resistant C. album were recorded in a third of surveyed farms and nicosulfuron-resistant D. sanguinalis in a sixth. Half of Waikato farms and a quarter of Bay of Plenty farms (no Hawkes Bay or Wellington farms) had atrazine-resistant C. album. Dicamba-resistant C. album were not detected, nor were atrazine-resistant P. maculosa. Nicosulfuron resistant D. sanguinalis was recorded in 19% of Waikato farms, 6% of Bay of Plenty farms and 9% of Hawkes Bay farms (no Wellington farms). Amaranthus spp., Fallopia convolvulus, Persicaria spp., Solanum spp., Echinochloa crus-galli, Panicum spp. and Setaria spp. were not resistant to any of the herbicides tested. Twenty-nine to 52% of maize farms in the North Island are estimated to have herbicide resistant weeds. Resistance is common in maize farms in Waikato and western Bay of Plenty. Resistance is rare in southern regions, with only one instance of nicosulfuron-resistant D. sanguinalis and no resistant C. album. Most annual weeds in maize are not resistant to herbicides; although atrazine resistant C. album is widespread, it is currently controlled with alternative herbicides. Resistant D. sanguinalis appears to be an emerging problem. [ABSTRACT FROM AUTHOR]