The aims of this study were to examine indicators of socioeconomic deprivation among secondary school students and to determine associations between household poverty, neighbourhood deprivation and health indicators. Data were from a nationally representative sample of 8500 secondary school students in New Zealand who participated in a health survey in 2012. Latent class analyses were used to group students by household poverty based on nine indicators of household socioeconomic deprivation: no car; no phone; no computer; their parent/s worry about not having enough money for food; more than two people sharing a bedroom; no holidays with their families; moving home more than twice that year; garages or living rooms used as bedrooms; and, no parent at home with employment. Multilevel generalized linear models were used to estimate the cross-level interaction between household poverty and neighbourhood deprivation with depressive symptoms, cigarette smoking and overweight/ obesity. Three groups of students were identified: 80 % of students had low levels of household poverty across all indicators; 15 % experienced moderate poverty; and 5 % experienced high levels of poverty. Depressive symptoms and cigarette smoking were 2–3 times higher in the poverty groups compared to student’s not experiencing poverty. There were also higher rates of overweight/ obesity among students in the poverty groups compared to students not experiencing poverty, but once covariates were accounted for the relationship was less clear. Of note, students experiencing poverty and living in affluent neighbourhoods reported higher levels of depressive symptoms and higher rates of cigarette smoking than students experiencing poverty and living in low socioeconomic neighbourhoods. This cross-level interaction was not seen for overweight/ obesity. Measures of household socioeconomic deprivation among young people should not be combined with neighbourhood measures of socioeconomic deprivation due to non-linear relationships with health and behaviour indicators. Policies are needed that address household poverty alongside efforts to reduce socioeconomic inequalities in neighbourhoods.

Although most adolescents are healthy, epidemiological studies show that a significant number experience mental health challenges, and that Indigenous and ethnic minority youth tend to have poorer mental health outcomes. However, ethnic classification in adolescence is complex due to increasing multi-ethnic identification, and little is known about how different classification methods affect research conclusions. This study used a nationally representative adolescent sample from Aotearoa New Zealand (N = 8275; ages 12–18; 55% female; 32% multi-ethnic) to investigate the effects that five ethnic classification methods have on substantive findings in three mental health outcomes: overall psychosocial difficulties, deliberate self-harm, and suicide attempts. The results showed that, depending on the classification method used, reported outcomes within the same nominal ethnic group varied by an effect size (d) of up to 0.12, and the reported magnitude of difference between nominal ethnic groups varied by an effect size (d) of up to 0.25. These effects are substantial given that they are solely due to a change in method. The impact that ethnic classification method has on substantive findings highlights the importance of criticality and transparency in research involving ethnicity data.

Ethnicity is an important variable in health and social science research, but working quantitatively with ethnicity data is complex because the construct is multifaceted, fluid, subjective, and political in nature. This necessitates careful consideration within the context of, and issues related to, the collection and classification of ethnicity data. Researchers’ methodological decisions regarding ethnicity data can impact substantive research outcomes and implications for policy and practice. This critical review provides an overview of the conceptualisation and sociohistorical context of ethnicity, followed by a thorough discussion of the methodological issues in the collection and analysis of ethnicity data with a focus on the Aotearoa New Zealand context. It then offers comprehensive guidance and recommendations for quantitative researchers. With an emphasis on researcher criticality, reflexivity, and the importance of upholding the data sovereignty of Indigenous and minoritised ethnic groups, this review equips data users with the information needed to conduct ethical, equitable, robust, and scientifically‐informed research involving ethnicity.

Engagement in further education, employment or training following the completion of compulsory schooling is an important predictor of adult life adjustment. As a key microsystemic context, supportive school environments can facilitate positive transitions, especially for disadvantaged youth who are at higher risk of underachievement and not engaging in further education, employment or training (NEET) in emerging adulthood. The present research consists of quantitative and qualitative analyses of secondary data of three student cohorts from a New Zealand boarding secondary school for males from disadvantaged backgrounds to investigate positive transition outcomes and experiences. The quantitative study (N = 178) compared participants’ educational attainment and NEET status across cohorts and with national statistics. Results showed that participants’ achievement and transition outcomes were consistently superior to the national comparison. The qualitative study (N = 38) examined the subjective experiences of a subsample of participants who transitioned to tertiary study and apprenticeship courses. These findings highlight the importance of cultivating students’ holistic development during the secondary school years. Implications for secondary schools are discussed.