Methods for structural sexism and population health research: Introducing a novel analytic framework to capture life-course and intersectional effects.

Accumulating evidence links structural sexism to gendered health inequities, yet methodological challenges have precluded comprehensive examinations into life-course and/or intersectional effects. To help address this gap, we introduce an analytic framework that uses sequential conditional mean models (SCMMs) to jointly account for longitudinal exposure trajectories and moderation by multiple dimensions of social identity/position, which we then apply to study how early life-course exposure to U.S. state-level structural sexism shapes mental health outcomes within and between gender groups. Data came from the Growing Up Today Study, a cohort of 16,875 children aged 9-14 years in 1996 who we followed through 2016. Using a composite index of relevant public policies and societal conditions (e.g., abortion bans, wage gaps), we assigned each U.S. state a year-specific structural sexism score and calculated participants' cumulative exposure by averaging the scores associated with states they had lived in during the study period, weighted according to duration of time spent in each. We then fit a series of SCMMs to estimate overall and group-specific associations between cumulative exposure from baseline through a given study wave and subsequent depressive symptomology; we also fit models using simplified (i.e., non-cumulative) exposure variables for comparison purposes. Analyses revealed that cumulative exposure to structural sexism: (1) was associated with significantly increased odds of experiencing depressive symptoms by the subsequent wave; (2) disproportionately impacted multiply marginalized groups (e.g., sexual minority girls/women); and (3) was more strongly associated with depressive symptomology compared to static or point-in-time exposure operationalizations (e.g., exposure in a single year). Substantively, these findings suggest that long-term exposure to structural sexism may contribute to the inequitable social patterning of mental distress among young people living in the U.S. More broadly, the proposed analytic framework represents a promising approach to examining the complex links between structural sexism and health across the life course and for diverse social groups.

The impact of the cost-of-living crisis on population health in the UK: rapid evidence review.

BACKGROUND: In the UK, unique and unforeseen factors, including COVID-19, Brexit, and Ukraine-Russia war, have resulted in an unprecedented cost of living crisis, creating a second health emergency. We present, one of the first rapid reviews with the aim of examining the impact of this current crisis, at a population level. We reviewed published literature, as well as grey literature, examining a broad range of physical and mental impacts on health in the short, mid, and long term, identifying those most at risk, impacts on system partners, including emergency services and the third sector, as well as mitigation strategies. METHODS: We conducted a rapid review by searching PubMed, Embase, MEDLINE, and HMIC (2020 to 2023). We searched for grey literature on Google and hand-searched the reports of relevant public health organisations. We included interventional and observational studies that reported outcomes of interventions aimed at mitigating against the impacts of cost of living at a population level. RESULTS: We found that the strongest evidence was for the impact of cold and mouldy homes on respiratory-related infections and respiratory conditions. Those at an increased risk were young children (0-4 years), the elderly (aged 75 and over), as well as those already vulnerable, including those with long-term multimorbidity. Further short-term impacts include an increased risk of physical pain including musculoskeletal and chest pain, and increased risk of enteric infections and malnutrition. In the mid-term, we could see increases in hypertension, transient ischaemic attacks, and myocardial infarctions, and respiratory illnesses. In the long term we could see an increase in mortality and morbidity rates from respiratory and cardiovascular disease, as well as increase rates of suicide and self-harm and infectious disease outcomes. Changes in behaviour are likely particularly around changes in food buying patterns and the ability to heat a home. System partners are also impacted, with voluntary sectors seeing fewer volunteers, an increase in petty crime and theft, alternative heating appliances causing fires, and an increase in burns and burn-related admissions. To mitigate against these impacts, support should be provided, to the most vulnerable, to help increase disposable income, reduce energy bills, and encourage home improvements linked with energy efficiency. Stronger links to bridge voluntary, community, charity and faith groups are needed to help provide additional aid and support. CONCLUSION: Although the CoL crisis affects the entire population, the impacts are exacerbated in those that are most vulnerable, particularly young children, single parents, multigenerational families. More can be done at a community and societal level to support the most vulnerable, and those living with long-term multimorbidity. This review consolidates the current evidence on the impacts of the cost of living crisis and may enable decision makers to target limited resources more effectively.

Underrepresentation of blind and deaf participants in the All of Us Research Program.

Blind and deaf individuals comprise large populations that often experience health disparities, with those from marginalized gender, racial, ethnic and low-socioeconomic communities commonly experiencing compounded health inequities. Including these populations in precision medicine research is critical for scientific benefits to accrue to them. We assessed representation of blind and deaf people in the All of Us Research Program (AoURP) 2018-2023 cohort of participants who provided electronic health records and compared it with the Centers for Disease Control and Prevention 2018 national estimates by key demographic characteristics and intersections thereof. Blind and deaf AoURP participants are considerably underrepresented in the cohort, especially among working-age adults (younger than age 65 years), as well as Asian and multi-racial participants. Analyses show compounded underrepresentation at the intersection of multiple marginalization (that is, racial or ethnic minoritized group, female sex, low education and low income), most substantively for working-age blind participants identifying as Black or African American female with education levels lower than high school (representing one-fifth of their national prevalence). Underrepresentation raises concerns about the generalizability of findings in studies that use these data and limited benefits for the already underserved blind and deaf populations.

The Impacts of the COVID-19 Pandemic on the Medical Expenditure Panel Survey.

The COVID-19 pandemic caused substantial disruptions in the field operations of all 3 major components of the Medical Expenditure Panel Survey (MEPS). The MEPS is widely used to study how policy changes and major shocks, such as the COVID-19 pandemic, affect insurance coverage, access, and preventive and other health care utilization and how these relate to population health. We describe how the MEPS program successfully responded to these challenges by reengineering field operations, including survey modes, to complete data collection and maintain data release schedules. The impact of the pandemic on response rates varied considerably across the MEPS. Investigations to date show little effect on the quality of data collected. However, lower response rates may reduce the statistical precision of some estimates. We also describe several enhancements made to the MEPS that will allow researchers to better understand the impact of the pandemic on US residents, employers, and the US health care system. (Am J Public Health. 2021;111(12):2157-2166. https://doi.org/10.2105/AJPH.2021.306534).

Trends in the Concentration and Distribution of Health Care Expenditures in the US, 2001-2018.

Importance: The concentration of health care expenditures has important implications for managing risk pools, drug benefit design, and care management. Objective: To examine trends in the concentration of health care spending in different population groups and expenditure categories in the US between 2001 and 2018. Design, Setting, and Participants: This study is a cross-sectional analysis of Medical Expenditure Panel Surveys (MEPS) collected between 2001 and 2018. The MEPS is a household survey of medical expenditures weighted to represent national estimates in the US. Respondents were a nationally representative sample of the US civilian noninstitutionalized population. Data analysis was performed from December 2020 to February 2021. Main Outcomes and Measures: The main outcome is the concentration of health care expenditures as measured by the cumulative percentage of health expenditure vs percentage of ranked population. This study reports trends in the distribution of populations across 4 concentration curve parameters: top 50% expenditure (high spenders), next 49% expenditure (medium spenders), next 1% expenditure (low spenders), and nonspenders. Results: The mean sample size of the MEPS surveys used in the analysis was 34 539 individuals, and the sample size varied between 30 461 and 39 165 individuals over the years studied. On the basis of data from 30 461 MEPS respondents (15 867 women [52.1%]; mean [SD] age, 38.9 [24.0] years) in 2018, the top 4.6% (95% CI, 4.3%-4.9%) of the US population by spending accounted for 50% of health care expenditures. Although this fraction varied across population groups or expenditure categories, it remained remarkably stable over time with one exception: the concentration of spending on prescription drugs. In 2001, one-half of all expenditures on prescription drugs were concentrated in 6.0% (95% CI, 5.6%-6.4%) of the US population, but by 2018, this proportion had decreased to 2.3% (95% CI, 2.1%-2.5%). This change does not appear to be associated with a change in the overall share of prescription drug expenses, which increased by only a small amount, from 20.4% in 2001 to 24.8% in 2018. Conclusions and Relevance: The overall concentration of health care expenditures remained stable between 2001 and 2018, but these findings suggest that there has been a sharp increase in the concentration of spending on prescription drugs in the US. This coincides with the genericization of many primary care drugs, along with a shift in focus of the biopharmaceutical industry toward high-cost specialty drugs targeted at smaller populations. If this trend continues, it will have implications for the minimum scale of risk-bearing and drug management needed to operate efficiently, as well as the optimal cost-sharing features of insurance products.

Resting Energy Expenditure and Related Factors in 6- to 9-Year-Old Southern African Children of Diverse Population Groups.

Lower resting energy expenditure (REE) may partially explain the disproportionate prevalence of overweight/obesity among black African women. As no previous studies have investigated the REE of Southern African (South. Afr.) children, we aimed to determine, by sex and population group, the REE of 6- to 9-year-old urban school children. In a cross-sectional study with quota sampling, REE was measured with indirect calorimetry (IC). Confounders considered were: body composition (BC) (fat-free mass (FFM), FFM index, fat mass (FM), FM index), assessed using multifrequency bioelectrical impedance analysis, and physical activity (PA) measured with a pedometer. Multivariate regression was used to calculate REE adjusted for phenotypes (BC, z-scores of weight-for-age, height-for-age, body mass index-for-age) and PA. Sex and population differences in REE were determined with two-way ANOVA. Ninety-four healthy children (59.6% girls; 52.1% black) with similar socioeconomic status and PA opportunities participated. Despite BC variations, sex differences in REE were not significant (41 kcal/day; P = 0.375). The REE of black participants was lower than of white (146 kcal/day; P = 0.002). When adjusted for FFM and HFA z-score, the differences in REE declined but remained clinically meaningful at 91 kcal/day (P = 0.039) and 82 kcal/day (P = 0.108), respectively. We recommend the development of population-specific REE prediction equations for South. Afr. children.

Health and health care access in the US transgender population health (TransPop) survey.

BACKGROUND: Probability and nonprobability-based studies of US transgender persons identify different disparities in health and health care access. OBJECTIVES: We used TransPop, the first US national probability survey of transgender persons, to describe and compare measures of health and health access among transgender, nonbinary, and cisgender participants. We directly compared the results with 2015 US Transgender Survey (USTS) data and with previously published analyses from the Behavioral Risk Factor Surveillance System (BRFSS). METHODS: All participants were screened by Gallup Inc., which recruited a probability sample of US adults. Transgender people were identified using a two-step screening process. Eligible participants completed self-administered questionnaires (transgender n = 274, cisgender n = 1162). We obtained weighted proportions/means, then tested for differences between gender groups. Logistic regression was performed to evaluate associations. Bivariate analyses were conducted using the weighted USTS data set for shared variables in USTS and TransPop. RESULTS: Transgender participants were younger and more racially diverse compared to the cisgender group. Despite equally high insurance coverage, transgender people more often avoided care due to cost concerns. Nonbinary persons were less likely to access transgender-related health care providers/clinics than transgender men and women. Transgender respondents more often rated their health as fair/poor, with more frequently occuring poor physical and mental health days compared to cisgender participants. Health conditions including HIV, emphysema, and ulcer were higher among transgender people. TransPop and USTS, unlike BRFSS-based analyses, showed no differences in health or health access. DISCUSSION: Transgender persons experience health access disparities centered on avoidance of care due to cost beyond insured status. Health disparities correspond with models of minority stress, with nonbinary persons having distinct health/health access patterns. Despite different sampling methods, USTS and TransPop appear more similar than BRFSS studies regarding health/health access. CONCLUSION: Future research should elucidate health care costs for transgender and nonbinary people, while addressing methodology in national studies of transgender health.

Minimizing Population Health Loss in Times of Scarce Surgical Capacity During the Coronavirus Disease 2019 Crisis and Beyond: A Modeling Study.

OBJECTIVES: Coronavirus disease 2019 has put unprecedented pressure on healthcare systems worldwide, leading to a reduction of the available healthcare capacity. Our objective was to develop a decision model to estimate the impact of postponing semielective surgical procedures on health, to support prioritization of care from a utilitarian perspective. METHODS: A cohort state-transition model was developed and applied to 43 semielective nonpediatric surgical procedures commonly performed in academic hospitals. Scenarios of delaying surgery from 2 weeks were compared with delaying up to 1 year and no surgery at all. Model parameters were based on registries, scientific literature, and the World Health Organization Global Burden of Disease study. For each surgical procedure, the model estimated the average expected disability-adjusted life-years (DALYs) per month of delay. RESULTS: Given the best available evidence, the 2 surgical procedures associated with most DALYs owing to delay were bypass surgery for Fontaine III/IV peripheral arterial disease (0.23 DALY/month, 95% confidence interval [CI]: 0.13-0.36) and transaortic valve implantation (0.15 DALY/month, 95% CI: 0.09-0.24). The 2 surgical procedures with the least DALYs were placing a shunt for dialysis (0.01, 95% CI: 0.005-0.01) and thyroid carcinoma resection (0.01, 95% CI: 0.01-0.02). CONCLUSION: Expected health loss owing to surgical delay can be objectively calculated with our decision model based on best available evidence, which can guide prioritization of surgical procedures to minimize population health loss in times of scarcity. The model results should be placed in the context of different ethical perspectives and combined with capacity management tools to facilitate large-scale implementation.

Excessive Health Care Spending Fails to Improve U.S. Population Health.

A recent analysis highlights waste and missed opportunities to improve outcomes.

The Gini coefficient as a useful measure of malaria inequality among populations.

BACKGROUND: Understanding inequality in infectious disease burden requires clear and unbiased indicators. The Gini coefficient, conventionally used as a macroeconomic descriptor of inequality, is potentially useful to quantify epidemiological heterogeneity. With a potential range from 0 (all populations equal) to 1 (populations having maximal differences), this coefficient is used here to show the extent and persistence of inequality of malaria infection burden at a wide variety of population levels. METHODS: First, the Gini coefficient was applied to quantify variation among World Health Organization world regions for malaria and other major global health problems. Malaria heterogeneity was then measured among countries within the geographical sub-region where burden is greatest, among the major administrative divisions in several of these countries, and among selected local communities. Data were analysed from previous research studies, national surveys, and global reports, and Gini coefficients were calculated together with confidence intervals using bootstrap resampling methods. RESULTS: Malaria showed a very high level of inequality among the world regions (Gini coefficient, G = 0.77, 95% CI 0.66-0.81), more extreme than for any of the other major global health problems compared at this level. Within the most highly endemic geographical sub-region, there was substantial inequality in estimated malaria incidence among countries of West Africa, which did not decrease between 2010 (G = 0.28, 95% CI 0.19-0.36) and 2018 (G = 0.31, 0.22-0.39). There was a high level of sub-national variation in prevalence among states within Nigeria (G = 0.30, 95% CI 0.26-0.35), contrasting with more moderate variation within Ghana (G = 0.18, 95% CI 0.12-0.25) and Sierra Leone (G = 0.17, 95% CI 0.12-0.22). There was also significant inequality in prevalence among local village communities, generally more marked during dry seasons when there was lower mean prevalence. The Gini coefficient correlated strongly with the standard coefficient of variation, which has no finite range. CONCLUSIONS: The Gini coefficient is a useful descriptor of epidemiological inequality at all population levels, with confidence intervals and interpretable bounds. Wider use of the coefficient would give broader understanding of malaria heterogeneity revealed by multiple types of studies, surveys and reports, providing more accessible insight from available data.

The Use of Penalized Regression Analysis to Identify County-Level Demographic and Socioeconomic Variables Predictive of Increased COVID-19 Cumulative Case Rates in the State of Georgia.

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables from collinear groups. Twelve variables correlated to cumulative case rates (for cases reported by 1 August 2020) with an adjusted r squared of 0.4525. As time progressed in the pandemic, correlation of demographic and socioeconomic factors to cumulative case rates increased, as did number of variables selected. Findings indicate the social determinants of health and demographic factors continue to predict case rates of COVID-19 at the county-level as the pandemic evolves. This research contributes to the growing body of evidence that health disparities continue to widen, disproportionality affecting vulnerable populations.

Intestinal microbiology shapes population health impacts of diet and lifestyle risk exposures in Torres Strait Islander communities.

Poor diet and lifestyle exposures are implicated in substantial global increases in non-communicable disease burden in low-income, remote, and Indigenous communities. This observational study investigated the contribution of the fecal microbiome to influence host physiology in two Indigenous communities in the Torres Strait Islands: Mer, a remote island where a traditional diet predominates, and Waiben a more accessible island with greater access to takeaway food and alcohol. Counterintuitively, disease markers were more pronounced in Mer residents. However, island-specific differences in disease risk were explained, in part, by microbiome traits. The absence of Alistipes onderdonkii, for example, significantly (p=0.014) moderated island-specific patterns of systolic blood pressure in multivariate-adjusted models. We also report mediatory relationships between traits of the fecal metagenome, disease markers, and risk exposures. Understanding how intestinal microbiome traits influence response to disease risk exposures is critical for the development of strategies that mitigate the growing burden of cardiometabolic disease in these communities.

The social, economic, political, and genetic value of race and ethnicity in 2020.

Disparities across racial and ethnic groups are present for a range of health outcomes. In this opinion piece, we consider the origin of racial and ethnic groupings, a history that highlights the sociopolitical nature of these terms. Indeed, the terms race and ethnicity exist purely as social constructs and must not be used interchangeably with genetic ancestry. There is no scientific evidence that the groups we traditionally call "races/ethnicities" have distinct, unifying biological or genetic basis. Such a focus runs the risk of compounding equity gaps and perpetuating erroneous conclusions. That said, we suggest that the terms race and ethnicity continue to have purpose as lenses through which to quantify and then close racial and ethnic disparities. Understanding the root cause of such health disparities-namely, longstanding racism and ethnocentrism-could promote interventions and policies poised to equitably improve population health.

Well-Being in the Nation: A Living Library of Measures to Drive Multi-Sector Population Health Improvement and Address Social Determinants.

Policy Points Well-being In the Nation (WIN) offers the first parsimonious set of vetted common measures to improve population health and social determinants across sectors at local, state, and national levels and is driven by what communities need to improve health, well-being, and equity. The WIN measures were codesigned with more than 100 communities, federal agencies, and national organizations across sectors, in alignment with the National Committee on Vital and Health Statistics, the Foundations for Evidence-Based Policymaking Act, and Healthy People 2030. WIN offers a process for a collaborative learning measurement system to drive a learning health and well-being system across sectors at the community, state, and national levels. The WIN development process identified critical gaps and opportunities in equitable community-level data infrastructure, interoperability, and protections that could be used to inform the Federal Data Strategy.

Commercial determinants of health: an ethical exploration.

OBJECTIVES: This paper seeks to contribute toward a better understanding of commercial determinants of health by proposing a set of ethical principles that can be used by researchers and other health actors in understanding and addressing Commercial Determinants of Health (CDoH). METHODS: The paper is mainly based on a systematic review and qualitative analysis of the existing literature on CDoH and public health ethics frameworks. We conducted searches using selected search engines (Google Scholar and Pubmed). For ethical challenges relating to CDOH, our searches in Google Scholar yielded 17 papers that discussed ethical challenges that affect CDoH. For ethical frameworks relevant for CDOH, our searches in Google Scholar and Pubmed yielded 15 papers that clearly described bioethical models including relevant ethical principles. Additionally, we consulted eight experts working on CDoH. Through these two methods, we were able to identify ethical challenges as well as norms and values related to CDoH that we offer as candidates to comprise a foundational ethics framework for CDoH. RESULTS: Discussing risk factors associated with CDH frequently brings public health into conflict with the interests of industry actors in the food, automobile, beverage, alcohol, ammunition, gaming and tobacco industries including conflict between profit-making and public health. We propose the following candidate ethical principles that can be used in addressing CDoH: moral responsibility, nonmaleficence, social justice and equity, consumer sovereignty, evidence-informed actions, responsiveness, accountability, appropriateness, transparency, beneficence and holism. CONCLUSIONS: We hope that this set of guiding principles will generate wider global debate on CDoH and help inform ethical analyses of corporate actions that contribute to ill health and policies aimed at addressing CDoH. These candidate principles can guide researchers and health actors including corporations in addressing CDoH.

Equity impacts of interventions to increase physical activity among older adults: a quantitative health impact assessment.

BACKGROUND: Behavioural interventions may increase social inequalities in health. This study aimed to project the equity impact of physical activity interventions that have differential effectiveness across education groups on the long-term health inequalities by education and gender among older adults in Germany. METHODS: We created six intervention scenarios targeting the elderly population: Scenarios #1-#4 applied realistic intervention effects that varied by education (low, medium high). Under scenario #5, all older adults adapted the physical activity pattern of those with a high education. Under scenario #6, all increased their physical activity level to the recommended 300 min weekly. The number of incident ischemic heart disease, stroke and diabetes cases as well as deaths from all causes under each of these six intervention scenarios was simulated for males and females over a 10-year projection period using the DYNAMO-HIA tool. Results were compared against a reference-scenario with unchanged physical activity. RESULTS: Under scenarios #1-#4, approximately 3589-5829 incident disease cases and 6248-10,320 deaths could be avoided among males over a 10-year projection period, as well as 4381-7163 disease cases and 6914-12,605 deaths among females. The highest reduction for males would be achieved under scenario #4, under which the intervention is most effective for those with a high education level. Scenario #4 realizes 2.7 and 2.4% of the prevented disease cases and deaths observed under scenario #6, while increasing inequalities between education groups. In females, the highest reduction would be achieved under scenario #3, under which the intervention is most effective amongst those with low levels of education. This scenario realizes 2.7 and 2.9% of the prevented disease cases and deaths under scenario #6, while decreasing inequalities between education groups. Under scenario #5, approximately 31,687 incident disease cases and 59,068 deaths could be prevented among males over a 10-year projection period, as well as 59,173 incident disease cases and 121,689 deaths among females. This translates to 14.4 and 22.2% of the prevented diseases cases among males and females under scenario #6, and 13.7 and 27.7% of the prevented deaths under scenario #6. CONCLUSIONS: This study shows how the overall population health impact varies depending on how the intervention-induced physical activity change differs across education groups. For decision-makers, both the assessment of health impacts overall as well as within a population is relevant as interventions with the greatest population health gain might be accompanied by an unintended increase in health inequalities.

The Race to the Bottom: Wisconsin's Long-Term Trends in Health Rankings.

BACKGROUND: Wisconsin's health ranking dropped from 7th healthiest in 1990 to 23rd in 2018. The purpose of this paper is to identify the contributory factors to this decline. METHODS: Trends in Wisconsin's health rank for 1990 to 2018 were compared overall and for only identical measures used in both years. RESULTS: Of the identical measures used in both years (n=10), the median rank declined from 8.5 (range 6-21) in 1990 to 19 (range 9-43) in 2018, with the greatest declines for infectious diseases, infant mortality, and smoking. The ranks were lower in 2018 for the similar measures used and for measures used only in 2018 compared to measures used only in 1990. DISCUSSION: Wisconsin's drop in health ranking is real and calls for action to address the root causes.

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.