The estimated health impact of alcohol interventions in New Zealand: A modelling study.

AIMS: To estimate the health impacts of key modelled alcohol interventions among Maori (indigenous peoples) and non-Maori in New Zealand (NZ). DESIGN: Multi-stage life-table intervention modelling study. We modelled two scenarios: (1) business-as-usual (BAU); and (2) an intervention package scenario that included a 50% alcohol tax increase, outlet density reduction from 63 to five outlets per 100 000 people, outlet hours reduction from 112 to 50 per week and a complete ban on all forms of alcohol marketing. SETTING AND PARTICIPANTS: The model's population replicates the 2018 NZ population by ethnicity (Maori/non-Maori), age and sex. MEASUREMENTS: Alcohol consumption was estimated using nationally representative survey data combined with sales data and corrected for tourist and unrecorded consumption. Disease incidence, prevalence and mortality were calculated using Ministry of Health data. We used dose-response relationships between alcohol and illness from the 2016 Global Burden of Disease study and calculated disability rates for each illness. Changes in consumption were based on the following effect sizes: total intervention package [-30.3%, standard deviation (SD) = 0.02); tax (-7.60%, SD = 0.01); outlet density (-8.64%, SD = 0.01); outlet hours (-9.24%, SD = 0.01); and marketing (-8.98%, SD = 0.02). We measured health gain using health-adjusted life years (HALYs) and life expectancy. FINDINGS: Compared with the BAU scenario, the total alcohol intervention package resulted in 726 000 [95% uncertainty interval (UI) = 492 000-913 000] HALYs gained during the life-time of the modelled population. Maori experienced greater HALY gains compared with non-Maori (0.21, 95% UI = 0.14-0.26 and 0.16, 95% UI = 0.11-0.20, respectively). When modelled individually, each alcohol intervention within the intervention package produced similar health gains (~200 000 HALYs per intervention) owing to the similar effect sizes. CONCLUSIONS: Modelled interventions for increased alcohol tax, reduced availability of alcohol and a ban on alcohol marketing among Maori and non-Maori in New Zealand (NZ) suggest substantial population-wide health gains and reduced health inequities between Maori and non-Maori.

The Epidemiology of Domain-Specific Physical Activity in New Zealand Adults: A Nationally Representative Cross-Sectional Survey.

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. Maori 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.

Determinants of Future Physical Activity Participation in New Zealand Adolescents across Sociodemographic Groups: A Descriptive Study.

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. Maori 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.

Do poverty and wealth look the same the world over? A comparative study of 12 cities from five high-income countries using street images.

Urbanization and inequalities are two of the major policy themes of our time, intersecting in large cities where social and economic inequalities are particularly pronounced. Large scale street-level images are a source of city-wide visual information and allow for comparative analyses of multiple cities. Computer vision methods based on deep learning applied to street images have been shown to successfully measure inequalities in socioeconomic and environmental features, yet existing work has been within specific geographies and have not looked at how visual environments compare across different cities and countries. In this study, we aim to apply existing methods to understand whether, and to what extent, poor and wealthy groups live in visually similar neighborhoods across cities and countries. We present novel insights on similarity of neighborhoods using street-level images and deep learning methods. We analyzed 7.2 million images from 12 cities in five high-income countries, home to more than 85 million people: Auckland (New Zealand), Sydney (Australia), Toronto and Vancouver (Canada), Atlanta, Boston, Chicago, Los Angeles, New York, San Francisco, and Washington D.C. (United States of America), and London (United Kingdom). Visual features associated with neighborhood disadvantage are more distinct and unique to each city than those associated with affluence. For example, from what is visible from street images, high density poor neighborhoods located near the city center (e.g., in London) are visually distinct from poor suburban neighborhoods characterized by lower density and lower accessibility (e.g., in Atlanta). This suggests that differences between two cities is also driven by historical factors, policies, and local geography. Our results also have implications for image-based measures of inequality in cities especially when trained on data from cities that are visually distinct from target cities. We showed that these are more prone to errors for disadvantaged areas especially when transferring across cities, suggesting more attention needs to be paid to improving methods for capturing heterogeneity in poor environment across cities around the world. Supplementary Information: The online version contains supplementary material available at 10.1140/epjds/s13688-023-00394-6.

Differences in physical activity participation among young adults in Aotearoa New Zealand.

BACKGROUND: The purpose of this study was to examine socio-demographic differences in physical activity (aerobic and muscle-strengthening) among young adults (18-24 years). METHODS: Data collected between 2017-2019 as a part of Sport New Zealand's Active NZ survey were examined using logistic regression analyses to determine the odds of participants meeting aerobic, muscle-strengthening and combined physical activity recommendations. Gender, ethnicity, employment/student status, disability status, and socio-economic deprivation were included as explanatory variables in analyses. RESULTS: The proportion of young adults meeting recommendations varied according to physical activity type (aerobic:63.2%; strength:40.1%; combined:37.2%). Young adults not employed/studying had lower odds of meeting recommendations than those full-time employed (OR = 0.43 [0.34-0.54]). Physical activity levels differ according to gender and this intersects with ethnicity, employment/student status, and social deprivation. For example, the odds of Pasifika young adults meeting combined physical activity recommendations compared to Europeans were not different (OR = 0.95 [0.76-1.19]), but when stratified by gender the odds were significantly higher for men (OR = 1.55 [1.11-2.16]) and significantly lower for women (OR = 0.64 [0.47-0.89]. Similarly, young adults in high deprivation areas had lower odds of meeting combined physical activity recommendations than those in low deprivation areas (OR = 0.81 [0.68-0.95]), but this was mainly due to the difference among women (OR = 0.68 [0.54-0.85]) as there was no difference among men (OR = 0.97 [0.76-1.25]). CONCLUSIONS: Intersections between socio-demographic characteristics should be considered when promoting physical activity among young adults in Aotearoa New Zealand, particularly young adults not employed/studying, and young women who live in deprived areas or identify as Asian or Pasifika. Tailored approaches according to activity type for each of these groups are required.

We still don't count: the under-counting and under-representation of Maori in health and disability sector data.

AIM: To examine ethnicity data quality; in particular, the representation and potential under-counting of Maori in health and disability sector data, as well as implications for inequities. METHODS: Maori and non-Maori ethnicity data are analysed at: 1) a population aggregate level across multiple 2018 datasets (Estimated Resident Population, Census Usually Resident Population, Health Service User (HSU) population and Primary Health Organisation (PHO) enrolments); and 2) an individual level for those linked in PHO and 2018 Census datasets. Ethnicity is drawn from the National Health Index (NHI) in health datasets and variations by age and gender are explored. RESULTS: Aggregate analyses show that Maori are considerably under-represented in HSU and PHO data. In linked analysis Maori were under-counted on the NHI by 16%. Under-representation in data and under-counting occur across both genders but are more pronounced for Maori men with variations by age. CONCLUSION: High quality ethnicity data are fundamental for understanding and monitoring Maori health and health inequities as well as in the provision of targeted services and interventions that are responsive to Maori aspirations and needs. The continued under-counting of Maori in health and disability sector data is a breach of Te Tiriti o Waitangi and must be addressed with urgency.

Potential effect of real-world junk food and sugar-sweetened beverage taxes on population health, health system costs and greenhouse gas emissions in New Zealand: a modelling study.

Poor diet is a major risk factor for excess weight gain and obesity-related diseases, including cardiovascular diseases, type 2 diabetes mellitus, osteoarthritis and several cancers. This paper aims to assess the potential impacts of real-world food and beverage taxes on change in dietary risk factors, health gains (in quality-adjusted life years (QALYs)), health system costs and greenhouse gas (GHG) emissions as if they had all been implemented in New Zealand (NZ). Ten taxes or tax packages were modelled. A proportional multistate life table model was used to predict resultant QALYs and costs over the remaining lifespan of the NZ population alive in 2011, as well as GHG emissions. QALYs ranged from 12.5 (95% uncertainty interval (UI) 10.2 to 15.0; 3% discount rate) per 1000 population for the import tax on sugar-sweetened beverages (SSB) in Palau to 143 (95% UI 118 to 171) per 1000 population for the excise duties on saturated fat, chocolate and sweets in Denmark, while health expenditure savings ranged from 2011 NZ$245 (95% UI 188 to 310; 2020 US$185) per capita to NZ$2770 (95% UI 2140 to 3480; US$2100) per capita, respectively. The modelled taxes resulted in decreases in GHG emissions from baseline diets, ranging from -0.2% for the tax on SSB in Barbados to -2.8% for Denmark's tax package. There is strong evidence for the implementation of food and beverage tax packages in NZ or similar high-income settings.

Comparing health gains, costs and cost-effectiveness of 100s of interventions in Australia and New Zealand: an online interactive league table.

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.

Estimating cardiovascular health gains from eradicating indoor cold in Australia.

BACKGROUND: Exposure to cold indoor temperature (< 18 degrees Celsius) increases cardiovascular disease (CVD) risk and has been identified by the WHO as a source of unhealthy housing. While warming homes has the potential to reduce CVD risk, the reduction in disease burden is not known. We simulated the population health gains from reduced CVD burden if the temperature in all Australian cold homes was permanently raised from their assumed average temperature of 16 degrees Celsius to 20 degrees Celsius. METHODS: The health effect of eradicating cold housing through reductions in CVD was simulated using proportional multistate lifetable model. The model sourced CVD burden and epidemiological data from Australian and Global Burden of Disease studies. The prevalence of cold housing in Australia was estimated from the Australian Housing Conditions Survey. The effect of cold indoor temperature on blood pressure (and in turn stroke and coronary heart disease) was estimated from published research. RESULTS: Eradication of exposure to indoor cold could achieve a gain of undiscounted one and a half weeks of additional health life per person alive in 2016 (base-year) in cold housing through CVD alone. This equates to 0.447 (uncertainty interval: 0.064, 1.34; 3% discount rate) HALYs per 1,000 persons over remainder of their lives through CVD reduction. Eight percent of the total health gains are achievable between 2016 and 2035. Although seemingly modest, the gains outperform currently recommended CVD interventions including persistent dietary advice for adults 5-9% 5 yr CVD risk (0.017 per 1000 people, UI: 0.01, 0.027) and persistent lifestyle program for adults 5-9% 5 yr CVD risk (0.024, UI: 0.01, 0.027). CONCLUSION: Cardiovascular health gains alone achievable through eradication of cold housing are comparable with real-life lifestyle and dietary interventions. The potential health gains are even greater given cold housing eradication will also improve respiratory and mental health in addition to cardiovascular disease.

Can a Greenhouse Gas Emissions Tax on Food also Be Healthy and Equitable? A Systemised Review and Modelling Study from Aotearoa New Zealand.

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 Maori. 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.

The Impact of Transport on Population Health and Health Equity for Maori in Aotearoa New Zealand: A Prospective Burden of Disease Study.

BACKGROUND: The land transport system influences health via a range of pathways. This study aimed to quantify the amount and distribution of health loss caused by the current land transport system in Aotearoa New Zealand (NZ) through the pathways of road injury, air pollution and physical inactivity. METHODS: We used an existing multi-state life table model to estimate the long-term health impacts (in health-adjusted life years (HALYs)) and changes in health system costs of removing road injury and transport related air pollution and increasing physical activity to recommended levels through active transport. Health equity implications were estimated using relative changes in HALYs and life expectancy for Maori and non-Maori. RESULTS: If the NZ resident population alive in 2011 was exposed to no further air pollution from transport, had no road traffic injuries and achieved at least the recommended weekly amount of physical activity through walking and cycling from 2011 onwards, 1.28 (95% UI: 1.11-1.5) million HALYs would be gained and $7.7 (95% UI: 10.2 to 5.6) billion (2011 NZ Dollars) would be saved from the health system over the lifetime of this cohort. Maori would likely gain more healthy years per capita than non-Maori, which would translate to small but important reductions (2-3%) in the present gaps in life expectancy. CONCLUSION: The current transport system in NZ, like many other car-dominated transport systems, has substantial negative impacts on health, at a similar level to the effects of tobacco and obesity. Transport contributes to health inequity, as Maori bear greater shares of the negative health impacts. Creating a healthier transport system would bring substantial benefits for health, society and the economy.

Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities.

BACKGROUND: Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities. We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply. METHODS: We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case-fatality rates by time-step of the model to ensure correct total population counts were retained at each step. To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality & morbidity rates, coronary heart disease incidence & case fatality rates; stroke incidence & case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups. The three interventions were then run on top of these scaled BAU scenarios. RESULTS: The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (HALYs) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population. CONCLUSION: Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.

Prescribing Smartphone Apps for Physical Activity Promotion in Primary Care: Modeling Study of Health Gain and Cost Savings.

BACKGROUND: Inadequate physical activity is a substantial cause of health loss worldwide, and this loss is attributable to diseases such as coronary heart disease, diabetes, stroke, and certain forms of cancer. OBJECTIVE: This study aims to assess the potential impact of the prescription of smartphone apps in primary care settings on physical activity levels, health gains (in quality-adjusted life years [QALYs]), and health system costs in New Zealand (NZ). METHODS: A proportional multistate lifetable model was used to estimate the change in physical activity levels and predict the resultant health gains in QALYs and health system costs over the remaining life span of the NZ population alive in 2011 at a 3% discount rate. RESULTS: The modeled intervention resulted in an estimated 430 QALYs gained (95% uncertainty interval 320-550), with net cost savings of 2011 NZ $2.2 million (2011 US $1.5 million) over the remaining life span of the 2011 NZ population. On a per capita basis, QALY gains were generally larger in women than in men and larger in Maori than in non-Maori. The health impact and cost-effectiveness of the intervention were highly sensitive to assumptions on intervention uptake and decay. For example, the scenario analysis with the largest benefits, which assumed a 5-year maintenance of additional physical activity levels, delivered 1750 QALYs and 2011 NZ $22.5 million (2011 US $15.1 million) in cost savings. CONCLUSIONS: The prescription of smartphone apps for promoting physical activity in primary care settings is likely to generate modest health gains and cost savings at the population level in this high-income country. Such gains may increase with ongoing improvements in app design and increased health worker promotion of the apps to patients.

Disease-related income and economic productivity loss in New Zealand: A longitudinal analysis of linked individual-level data.

BACKGROUND: Reducing disease can maintain personal individual income and improve societal economic productivity. However, estimates of income loss for multiple diseases simultaneously with thorough adjustment for confounding are lacking, to our knowledge. We estimate individual-level income loss for 40 conditions simultaneously by phase of diagnosis, and the total income loss at the population level (a function of how common the disease is and the individual-level income loss if one has the disease). METHODS AND FINDINGS: We used linked health tax data for New Zealand as a high-income country case study, from 2006 to 2007 to 2015 to 2016 for 25- to 64-year-olds (22.5 million person-years). Fixed effects regression was used to estimate within-individual income loss by disease, and cause-deletion methods to estimate economic productivity loss at the population level. Income loss in the year of diagnosis was highest for dementia for both men (US$8,882; 95% CI $6,709 to $11,056) and women ($7,103; $5,499 to $8,707). Mental illness also had high income losses in the year of diagnosis (average of about $5,300 per year for males and $4,100 per year for females, for 4 subcategories of: depression and anxiety; alcohol related; schizophrenia; and other). Similar patterns were evident for prevalent years of diagnosis. For the last year of life, cancers tended to have the highest income losses, (e.g., colorectal cancer males: $17,786, 95% CI $15,555 to $20,018; females: $14,192, $12,357 to $16,026). The combined annual income loss from all diseases among 25- to 64-year-olds was US$2.72 billion or 4.3% of total income. Diseases contributing more than 4% of total disease-related income loss were mental illness (30.0%), cardiovascular disease (15.6%), musculoskeletal (13.7%), endocrine (8.9%), gastrointestinal (7.4%), neurological (6.5%), and cancer (4.5%). The limitations of this study include residual biases that may overestimate the effect of disease on income loss, such as unmeasured time-varying confounding (e.g., divorce leading to both depression and income loss) and reverse causation (e.g., income loss leading to depression). Conversely, there may also be offsetting underestimation biases, such as income loss in the prodromal phase before diagnosis that is misclassified to "healthy" person time. CONCLUSIONS: In this longitudinal study, we found that income loss varies considerably by disease. Nevertheless, mental illness, cardiovascular, and musculoskeletal diseases stand out as likely major causes of economic productivity loss, suggesting that they should be prioritised in prevention programmes.

The potential of school-based physical education to increase physical activity in Aotearoa New Zealand children and young people: a modelling study.

AIMS: Regular physical activity (PA) is critical for children and young people's health and wellbeing. Schools are an important setting for promoting PA. This study aimed to examine prevalence of PA through physical education in New Zealand schools and the potential impact of increasing physical education on young people's PA levels. METHODS: We used data from the Active NZ Young People Survey of over 8,000 young people and modelled the impact of a hypothetical intervention that increased school-based physical education time to 2.5 hours (consistent with international best practice) on the distribution of PA. RESULTS: At baseline, 61.3% (95%UI 60.2-62.5) of young people were classified as being sufficiently active (7+ hours/week), 19.8% (95%UI 18.9-20.8) were moderately active, and 18.8% (95%CI 17.9-19.7) were minimally active. The intervention scenario would more than halve the prevalence of minimal activity to 8.1% (95%UI 7.5-8.8) and increase the proportion of sufficiently active young people to 68.4% (95%UI 67.3-69.5). CONCLUSION: Increasing time being active through physical education has the potential to reduce the prevalence of minimally active young people in New Zealand. Policies to support increased physical education time, such as time-based requirements, would increase PA levels.

Should prioritising health interventions be informed by modelling studies? The case of cancer control in Aotearoa New Zealand.

In this viewpoint, we suggest that policymakers should prioritise health interventions by using evidence around health gain, impact on equity, health-system costs and cost-effectiveness. We take the example of the new cancer control agency in New Zealand, Te Aho o Te Kahu, and argue that its decision-making can now be informed by many methodologically compatible epidemiological and health economic analyses. These analyses span primary prevention of cancer (eg, tobacco control, dietary and physical activity interventions and HPV vaccination), cancer screening, cancer treatment and palliative care. The largest health gain and cost-savings from the available modelling work for New Zealand are seen in nutrition and tobacco control interventions in particular. Many of these interventions have potentially greater per capita health gain for Maori than non-Maori and are also found to be cost saving for the health sector. In summary, appropriate prioritisation of interventions can potentially both maximise health benefits as well as making best use of government funding of the health system.

Hitting the Target but Missing the Point? Modelling Health and Economic Impacts of Different Approaches to Meeting the Global Action Plan for Physical Activity Target.

BACKGROUND: The World Health Organization launched the Global Action Plan for Physical Activity (GAPPA) in 2018, which set a global target of a 15% relative reduction in the prevalence of physical inactivity by 2030. This target, however, could be acheived in various ways. METHODS: We use an established multi-state life table model to estimate the health and economic gains that would accrue over the lifetime of the 2011 New Zealand population if the GAPPA target was met under two different approaches: (1) an equal shift approach where physical activity increases by the same absolute amount for everyone; (2) a proportional shift approach where physical activity increases proportionally to current activity levels. FINDINGS: An equal shift approach to meeting the GAPPA target would result in 197,000 health-adjusted life-years (HALYs) gained (95% uncertainty interval (UI) 152,000-246,000) and healthcare system cost savings of US$1.57b (95%UI $1.16b-$2.03b; 0% discount rate). A proportional shift to the GAPPA target would result in 158,000 HALYs (95%UI 127,000-194,000) and US$1.29billion (95%UI $0.99b-$1.64b) savings to the healthcare system. INTERPRETATION: Achieving the GAPPA target would result in large health gains and savings to the healthcare system. However, not all population approaches to increasing physical activity are equal-some population shifts bring greater health benefits. Our results demonstrate the need to consider the entire population physical activity distribution in addition to evaluating progress towards a target.

The World Health Organization launched the Global Action Plan for Physical Activity in 2018, which set a global target to reduce physical inactivity. We explored different ways in which this target could be met and found that some approaches to meeting the target would bring larger health gains and savings to the healthcare system than others.

Increased unemployment from the COVID-19 pandemic, what might be the adverse impacts on cardiovascular disease in Aotearoa/New Zealand and how might this be prevented?

Despite success with eliminating the COVID-19 pandemic in Aotearoa New Zealand (at least to early August 2020), the response to the pandemic threat has resulted in a range of negative social and economic impacts, including job losses. Understanding the health consequences of these impacts will be increasingly important in the 'recovery' phase. This article contributes to this understanding by exploring the relationship between unemployment and cardiovascular disease (CVD)-a major contributor to health loss in Aotearoa New Zealand. We reviewed the literature about the impact of unemployment on CVD. The totality of the evidence suggested that increased unemployment arising from economic shocks is associated with increased CVD incidence, particularly for middle-aged men. Continued monitoring and active policy responses are required to prevent increases in CVD (and other health outcomes) as a result of the COVID-19 pandemic response. For example, quantifying the CVD-related health loss from pandemic-associated unemployment, along with the health costs and impact on health inequalities, could help with government decision-making to reduce CVD burdens. This could be via intensifying tobacco control, regulating the food supply (eg, to reduce salt/sodium levels), and improving uptake of CVD preventive medications such as statins and anti-hypertensives.

Proportional multistate lifetable modelling of preventive interventions: concepts, code and worked examples.

Burden of Disease studies-such as the Global Burden of Disease (GBD) Study-quantify health loss in disability-adjusted life-years. However, these studies stop short of quantifying the future impact of interventions that shift risk factor distributions, allowing for trends and time lags. This methodology paper explains how proportional multistate lifetable (PMSLT) modelling quantifies intervention impacts, using comparisons between three tobacco control case studies [eradication of tobacco, tobacco-free generation i.e. the age at which tobacco can be legally purchased is lifted by 1 year of age for each calendar year) and tobacco tax]. We also illustrate the importance of epidemiological specification of business-as-usual in the comparator arm that the intervention acts on, by demonstrating variations in simulated health gains when incorrectly: (i) assuming no decreasing trend in tobacco prevalence; and (ii) not including time lags from quitting tobacco to changing disease incidence. In conjunction with increasing availability of baseline and forecast demographic and epidemiological data, PMSLT modelling is well suited to future multiple country comparisons to better inform national, regional and global prioritization of preventive interventions. To facilitate use of PMSLT, we introduce a Python-based modelling framework and associated tools that facilitate the construction, calibration and analysis of PMSLT models.

The effect of food taxes and subsidies on population health and health costs: a modelling study.

BACKGROUND: One possible policy response to the burden of diet-related disease is food taxes and subsidies, but the net health gains of these approaches are uncertain because of substitution effects between foods. We estimated the health and cost impacts of various food taxes and subsidies in one high-income country, New Zealand. METHODS: In this modelling study, we compared the effects in New Zealand of a 20% fruit and vegetable subsidy, of saturated fat, sugar and salt taxes (each set at a level that increased the total food price by the same magnitude of decrease from the fruit and vegetable subsidy), and of an 8% so-called junk food tax (on non-essential, energy-dense food). We modelled the effect of price changes on food purchases, the consequent changes in fruit and vegetable and sugar-sweetened beverage purchasing, nutrient risk factors, and body-mass index, and how these changes affect health status and health expenditure. The pre-intervention intake for 340 food groups was taken from the New Zealand National Nutrition Survey and the post-intervention intake was estimated using price and expenditure elasticities. The resultant changes in dietary risk factors were then propagated through a proportional multistate lifetable (with 17 diet-related diseases) to estimate the changes in health-adjusted life years (HALYs) and health system expenditure over the 2011 New Zealand population's remaining lifespan. FINDINGS: Health gains (expressed in HALYs per 1000 people) ranged from 127 (95% uncertainty interval 96-167; undiscounted) for the 8% junk food tax and 212 (102-297) for the fruit and vegetable subsidy, up to 361 (275-474) for the saturated fat tax, 375 (272-508) for the salt tax, and 581 (429-792) for the sugar tax. Health expenditure savings across the remaining lifespan per capita (at a 3% discount rate) ranged from US$492 (334-694) for the junk food tax to $2164 (1472-3122) for the sugar tax. INTERPRETATION: The large magnitude of the health gains and cost savings of these modelled taxes and subsidies suggests that their use warrants serious policy consideration. FUNDING: Health Research Council of New Zealand.