Anja Mizdrak

Introduction: Alcohol is responsible for substantial health loss and economic costs. This study aimed to estimate the health gains and health system costs of reducing alcohol consumption in Aotearoa New Zealand (A‐NZ). Methods: This study used the New Zealand Alcohol Intervention Model (NZ‐AIM) to estimate the impacts of: (i) a 30% reduction in alcohol consumption from a comprehensive intervention package; and (ii) the elimination of alcohol use. NZ‐AIM uses an open cohort approach that replicates the 2018 population by ethnicity (Māori/non‐Māori), age and sex. Results: Both elimination of alcohol consumption and a comprehensive intervention package result in large health gains for our open cohort over the next 60 years: 876,000HALYs (95% UI 432,000 to 1,233,000) and 512,000 HALYs (95% UI 358,000 to 637,000), respectively. With no discounting, the health system cost savings over 60 years are substantial: 2018NZ$3694million (95% UI −$1059m to $8682m) for elimination and $13million (95% UI −$1345m to $1606m) for the intervention package. In the first decade, the intervention package accrues NZ$552m (95% UI 362m to 737m) savings to the health system. Health system cost savings are sensitive to the discount rate and to whether costs associated with increased longevity are included. Discussion and Conclusions: The potential health gains and health system cost savings from the elimination or a reduction of alcohol consumption in Aotearoa New Zealand are large. The health system cost savings are substantial in the first few decades and then increase due to increased longevity. The findings provide additional evidence to support implementation of alcohol interventions aligning with the World Health Organization's SAFER framework.

Background: The present study aimed to estimate the alcohol-attributable mortality in Aotearoa New Zealand (Aotearoa) at varying levels of alcohol consumption to help inform low-risk-drinking guidelines (LRDGs) in Aotearoa. Methods: We used the New Zealand Alcohol Intervention Model—a multi-state life-table model parameterized with Aotearoa-specific alcohol and epidemiological data—to estimate the health risks associated with a daily alcohol intake of 0–100 g/day. We modelled a cohort of 12-year-olds for their life course, with exposure and disease rates fixed to 2018 levels. We used relative risk (RR) libraries developed by the World Health Organization (WHO) and Global Burden of Disease Study (GBD). The primary output was years of life lost (YLL), with 17.5 YLL used as a proxy for alcohol-related death, at lifetime-risk thresholds of 1-in-100 and 1-in-1000. Results: When the WHO RR library was used, males reached a 1-in-100 risk of alcohol-attributable death at 8.6 standard drinks (SDs, 10 g of ethanol) [95% uncertainty interval (UI) 3.1–12.0] per week, while females reach this threshold at 9.2 SDs (95% UI 3.7–12.4). The removal of health conditions receiving a one-star evidence rating from the GBD substantially reduced the number of SDs to 2.7 (95% UI 2.1–4.6) for males and 3.5 (95% UI 2.9–4.4) for females. Across all analyses, use of the GBD RR library led to more permissive results. Ethnicity-specific results showed that Māori breach the risk thresholds at lower levels of consumption than non-Māori. Conclusion: Our modelling demonstrates that the Aotearoa LRDGs are outdated and need updating to reflect contemporary understandings of the harms associated with alcohol use.

Aims: To estimate the alcohol‐attributable morbidity and mortality in New Zealand (NZ) as measured by deaths, cancer registrations, hospitalisations and Accident Compensation Corporation (ACC) injury claims. Design: Comparative risk assessment methodology. Setting and participants: The 2018 NZ population aged > 14 years, by ethnicity (Māori/non‐Māori), age and sex. Measurements: Alcohol‐attributable fractions (AAF) for 26 alcohol‐related conditions were generated in the International Model of Alcohol Harms and Policies (v3.0) using 2016 Global Burden of Disease Study relative risk functions and 2018 NZ alcohol exposure statistics. AAFs were applied to enumerated outcomes, with age–sex standardised rates computed using the 2018 estimated resident population. Primary results present net outcomes (allowing potential protective effects at low consumption where supported by risk curves); gross outcomes are presented in sensitivity analyses. Main outcomes included deaths, cancer registrations, publicly funded hospitalisations and ACC injury claims. Findings: In 2018, an estimated 901 deaths [95% uncertainty interval (UI) = 681–1104], 1250 cancer cases (95% UI = 1084−1383), 29 282 hospitalisations (95% UI = 25 713–32 318) and 128 963 ACC injury claims (95% UI = 114 324–140 681) were attributable to alcohol. Māori (Indigenous population in NZ) experienced a disproportionately high health burden: 4.7% of all deaths, 5.2% of all cancers, 3.4% of hospitalisations and 9.9% of ACC claims among Māori were attributable to alcohol, compared with 2.5%, 4.7%, 2.7% and 8.7% for non‐Māori, respectively. Age–sex standardised rates of alcohol‐attributable (AA) mortality, cancer registrations and hospitalisations were ~20–100% higher for Māori than non‐Māori. Males accounted for the majority of health harms (e.g. 83% of AA deaths and 64% of AA hospitalisations). Assuming no protective effects (gross outcomes), an estimated 1379 deaths (95% UI = 1202–1528) and 31 484 hospitalisations (95% UI = 28 209–34 204) were attributable to alcohol. Conclusions: Alcohol caused substantial, inequitable health loss in New Zealand in 2018. Māori bore a markedly higher age–sex standardised burden than non‐Māori.

Background: Surveillance of domain-specific physical activity (PA) helps to target interventions to promote PA. We examined the sociodemographic correlates of domain-specific PA in New Zealand adults. Methods: A nationally representative sample of 13,887 adults completed the International PA Questionnaire–long form in 2019/20. Three measures of total and domain-specific (leisure, travel, home, and work) PA were calculated: (1) weekly participation, (2) mean weekly metabolic energy equivalent minutes (MET-min), and (3) median weekly MET-min among those who undertook PA. Results were weighted to the New Zealand adult population. Results: The average contribution of domain-specific activity to total PA was 37.5% for work activities (participation = 43.6%; median participating MET-min = 2790), 31.9% for home activities (participation = 82.2%; median participating MET-min = 1185), 19.4% for leisure activities (participation = 64.7%; median participating MET-min = 933), and 11.2% for travel activities (participation = 64.0%; median MET-min among participants = 495). Women accumulated more home PA and less work PA than men. Total PA was higher in middle-aged adults, with diverse patterns by age within domains. Māori accumulated less leisure PA than New Zealand Europeans but higher total PA. Asian groups reported lower PA across all domains. Higher area deprivation was negatively associated with leisure PA. Sociodemographic patterns varied by measure. For example, gender was not associated with total PA participation, but men accumulated higher MET-min when taking part in PA than women. Conclusions: Inequalities in PA varied by domain and sociodemographic group. These results should be used to inform interventions to improve PA.

This cross-sectional study aimed to explore various determinants of future physical activity (PA) participation in adolescents across sociodemographic groups. Sociodemographic characteristics (age, gender, ethnicity, deprivation status, physical disability status) were assessed in a national sample (n = 6906) of adolescents (12–17 years old) between 2017 and 2020 in New Zealand. The determinants of future PA participation chosen for analysis included current indicators of PA participation (i.e., total time, number of types, number of settings). We also examined widely recognised modifiable intrapersonal (i.e., physical literacy) and interpersonal (i.e., social support) determinants of current and future PA behaviour, along with indicators of PA availability issues. Older adolescents scored worse across all determinants of future PA than younger adolescents, with a key transition point appearing at 14–15 years of age. Māori and Pacific ethnicities scored best across each determinant category on average, with Asian populations scoring the worst. Gender diverse adolescents scored substantially worse than male and female adolescents across every determinant. Physically disabled adolescents scored worse than non-disabled across all determinants. Adolescents from medium and high deprivation neighbourhoods scored similarly across most determinants of future PA participation and both tended to score worse than people from low deprivation neighbourhoods. A particular focus on the improvement of future PA determinants is warranted within adolescents who are older, Asian, gender diverse, physically disabled, and from medium to high deprivation neighbourhoods. Future investigation should prioritise the longitudinal tracking of PA behaviours over time and develop interventions that affect multiple future PA determinants across a range of sociodemographic backgrounds.

Background: This study compares the health gains, costs, and cost-effectiveness of hundreds of Australian and New Zealand (NZ) health interventions conducted with comparable methods in an online interactive league table designed to inform policy. Methods: A literature review was conducted to identify peer-reviewed evaluations (2010 to 2018) arising from the Australia Cost-Effectiveness research and NZ Burden of Disease Epidemiology, Equity and Cost-Effectiveness Programmes, or using similar methodology, with: health gains quantified as health-adjusted life years (HALYs); net health system costs and/or incremental cost-effectiveness ratio; time horizon of at least 10 years; and 3% to 5% discount rates. Results: We identified 384 evaluations that met the inclusion criteria, covering 14 intervention domains: alcohol; cancer; cannabis; communicable disease; cardiovascular disease; diabetes; diet; injury; mental illness; other non-communicable diseases; overweight and obesity; physical inactivity; salt; and tobacco. There were large variations in health gain across evaluations: 33.9% gained less than 0.1 HALYs per 1000 people in the total population over the remainder of their lifespan, through to 13.0% gaining > 10 HALYs per 1000 people. Over a third (38.8%) of evaluations were cost-saving. Conclusions: League tables of comparably conducted evaluations illustrate the large health gain (and cost) variations per capita between interventions, in addition to cost-effectiveness. Further work can test the utility of this league table with policy-makers and researchers.

Policies to mitigate climate change are essential. The objective of this paper was to estimate the impact of greenhouse gas (GHG) food taxes and assess whether such a tax could also have health benefits in Aotearoa NZ. We undertook a systemised review on GHG food taxes to inform four tax scenarios, including one combined with a subsidy. These scenarios were modelled to estimate lifetime impacts on quality-adjusted health years (QALY), health inequities by ethnicity, GHG emissions, health system costs and food costs to the individual. Twenty-eight modelling studies on food tax policies were identified. Taxes resulted in decreased consumption of the targeted foods (e.g., −15.4% in beef/ruminant consumption, N = 12 studies) and an average decrease of 8.3% in GHG emissions (N = 19 studies). The “GHG weighted tax on all foods” scenario had the largest health gains and costs savings (455,800 QALYs and NZD 8.8 billion), followed by the tax—fruit and vegetable subsidy scenario (410,400 QALYs and NZD 6.4 billion). All scenarios were associated with reduced GHG emissions and higher age standardised per capita QALYs for Māori. Applying taxes that target foods with high GHG emissions has the potential to be effective for reducing GHG emissions and to result in co-benefits for population health.

Introduction Policies to mitigate climate change are essential. The objective of this paper was to estimate the impact of greenhouse gas (GHG) food taxes and assess whether such a tax could also have health benefits and reduce ethnic inequalities in health in Aotearoa NZ. Methods We undertook a systemised review on GHG food taxes to inform four tax scenarios, including one combined with a subsidy. These scenarios were modelled to estimate lifetime impacts on quality adjusted health years (QALY), health inequities by ethnicity, GHG emissions, health system costs and food costs to the individual. Results 28 modelling studies on food tax policies were identified. Taxes resulted in decreased consumption of the targeted foods (e.g., -15.4% in beef/ruminant consumption, N=12 studies) and an average decrease of 8.3% in GHG emissions (N=19 studies). Using this review, we conceptualized four scenarios: a GHG weighted tax on all foods; a GHG weighted tax on food groups with the highest 50% of emissions (‘high emitters’); A GHG weighted tax on ‘high emitters’ combined with a fruit and vegetable subsidy; A 20% tax on ‘high emitters’. The ‘GHG weighted tax on all foods’ scenario had the largest health gains and costs savings (455,800 QALYs and NZ$8.8 billion), followed by the tax-subsidy scenario (410,400 QALYs and NZ$6.4 billion). All scenarios were associated with reduced GHG emissions (between 4.2% and 7.0% of the baseline GHG emissions from food). Age standardised per capita QALYs were between 1.6 and 2.1 times higher for Māori than non-Māori. Conclusion Applying taxes that target foods with high GHG emissions has the potential to be effective for reducing GHG emissions and to result in co-benefits for population health. Combining a GHG food tax with a fruit and vegetable subsidy may help reduce the negative effects on household food expenditure of such a tax. What is already known on this topic Modelling studies investigating the impact of food taxes have shown taxes aimed at high GHG emitting foods reduce consumption of ruminant meats and GHG emissions. No reviews of modelling studies of GHG motivated food taxes have been published. What this study adds Modelling studies are reviewed and summarised and used to inform modelling of four GHG motivated tax scenarios. Modelled results identify a tax/subsidy with positive impacts on population health (410,400 total or 93.2 quality adjusted life years per 1000 people over their lifetime), health system costs (NZD 6.4 billion savings), ethnic health equity (health gains were 1.6 times higher for NZ’s indigenous population, Māori than non-Māori), GHG emissions (−4.2%) and cost of diets (−0.5%). How this study might affect research, practice or policy Policymakers can use these findings in designing a food tax to benefit both climate and population health, utilising these detailed results on factors that affect population wellbeing.