Summary: The aim was to conduct a systematic review of real‐world sugar‐sweetened beverage (SSB) tax evaluations and examine the overall impact on beverage purchases and dietary intake by meta‐analysis. Medline, EconLit, Google Scholar, and Scopus databases were searched up to June 2018. SSB tax evaluations from any formal jurisdiction from cities to national governments were eligible if there was a comparison between pre–post tax (n = 11) or taxed and untaxed jurisdiction(s) (n = 6). The consumption outcome comprised sales, purchasing, and intake (reported by volume, energy, or frequency). Taxed and untaxed beverage consumption outcomes were examined separately by meta‐analysis with adjustment for the size of each tax. The study was registered at PROSPERO (CRD42018100620). The equivalent of a 10% SSB tax was associated with an average decline in beverage purchases and dietary intake of 10.0% (95% CI: −5.0% to −14.7%, n = 17 studies, 6 jurisdictions) with considerable heterogeneity between results (I² = 97%).The equivalent of a 10% SSB tax was also associated with a nonsignificant 1.9% increase in total untaxed beverage consumption (eg, water) (95% CI: −2.1% to 6.1%, n = 6 studies, 4 jurisdictions). Based on real‐world evaluations, SSB taxes introduced in jurisdictions around the world appear to have been effective in reducing SSB purchases and dietary intake.

Cancer makes up a large and increasing proportion of excess mortality for indigenous, marginalised and socioeconomically deprived populations, and much of this inequality is preventable. This study aimed to determine which cancers give rise to changing ethnic inequalities over time. New Zealand census data from 1981, 1986, 1991, 1996, 2001, and 2006, were all probabilistically linked to three to five subsequent years of mortality (68 million person-years) and cancer registrations (87 million person years) and weighted for linkage bias. Age-standardised rate differences (SRDs) for Māori (indigenous) and Pacific peoples, each compared to European/Other, were decomposed by cancer type. The absolute size and percentage of the cancer contribution to excess mortality increased from 1981–86 to 2006–11 in Māori males (SRD 72.5 to 102.0 per 100,000) and females (SRD 72.2 to 109.4), and Pacific females (SRD −9.8 to 42.2) each compared to European/Other. Specifically, excess mortality (SRDs) increased for breast cancer in Māori females (linear trend p < 0.01) and prostate (p < 0.01) and colorectal cancers (p < 0.01) in Māori males. The incidence gap (SRDs) increased for breast (Māori and Pacific females p < 0.01), endometrial (Pacific females p < 0.01) and liver cancers (Māori males p = 0.04), and for cervical cancer it decreased (Māori females p = 0.03). The colorectal cancer incidence gap which formerly favoured Māori, decreased for Māori males and females (p < 0.01). The greatest contributors to absolute inequalities (SRDs) in mortality in 2006–11 were lung cancer (Māori males 50 %, Māori females 44 %, Pacific males 81 %), breast cancer (Māori females 18 %, Pacific females 23 %) and stomach cancers (Māori males 9 %, Pacific males 16 %, Pacific females 20 %). The top contributors to the ethnic gap in cancer incidence were lung, breast, stomach, endometrial and liver cancer. A transition is occurring in what diseases contribute to inequalities. The increasing excess incidence and mortality rates in several obesity- and health care access-related cancers provide a sentinel warning of the emerging drivers of ethnic inequalities. Action to further address inequalities in cancer burden needs to be multi-pronged with attention to enhanced control of tobacco, obesity, and carcinogenic infectious agents, and focus on addressing access to effective screening and quality health care.

Cancer is increasingly responsible for the mortality gap between high and low socioeconomic position groups in high‐income countries. This study investigates which cancers are contributing more to socioeconomic gaps in mortality and how this changes over time.New Zealand census data from 1981, 1986, 1991, 1996, 2001 and 2006, were linked to three to five years of subsequent mortality and cancer registrations, resulting in 54 and 42 million years of follow‐up cancer incidence and mortality, respectively. Age‐ and ethnicity‐standardised cancer mortality rates and the slope index of inequality (SII) by income were calculated.The contribution of cancer to absolute inequalities (SII) in mortality increased from 16 to 27% for men and from 12 to 31% for women from 1981–84 to 2006–11, peaking in 1991–94 for men and in 1996–99 for women and then levelling off, parallel to peaks in lung cancer inequalities. Lung cancer was the largest driver of cancer inequality trends (49% of the cancer mortality gap in 1981–84 to 33% in 2006–11 for men and 32 to 33% for women) followed by colorectal cancer in men (2 to 11%) and breast cancer in women (declining from 44 to 13%). Women in the lowest income quintile experienced no decline in cancer mortality.The contribution of cancer to income inequalities in all‐cause mortality has expanded in this high‐income country. Action to address socioeconomic inequalities should prioritise equitable tobacco control, obesity control and improved access to cancer screening, early diagnosis and high quality treatment for those with the lowest incomes.

Holistic depiction of time-trends in average mortality rates, and absolute and relative inequalities, is challenging. We outline a typology for situations with falling average mortality rates (m↓; e.g., cardiovascular disease), rates stable over time (m-; e.g., some cancers), and increasing average mortality rates (m↑; e.g., suicide in some contexts). If we consider inequality trends on both the absolute (a) and relative (r) scales, there are 13 possible combination of m, a, and r trends over time. They can be mapped to graphs with relative inequality (log relative index of inequality [RII]; r) on the y axis, log average mortality rate on the x axis (m), and absolute inequality (slope index of inequality; SII; a) as contour lines. We illustrate this by plotting adult mortality trends: (1) by household income from 1981 to 2011 for New Zealand, and (2) by education for European countries. Types range from the “best” m↓a↓r↓ (average, absolute, and relative inequalities all decreasing; southwest movement in graphs) to the “worst” m↑a↑r↑ (northeast). Mortality typologies in New Zealand (all-cause, cardiovascular disease, nonlung cancer, and unintentional injury) were all m↓r↑ (northwest), but variable with respect to absolute inequality. Most European typologies were m↓r↑ types (northwest; e.g., Finland), but with notable exceptions of m-a↑r↑ (north; e.g., Hungary) and “best” or southwest m↓a↓r↓ for Spain (Barcelona) females. Our typology and corresponding graphs provide a convenient way to summarize and understand past trends in inequalities in mortality, and hold potential for projecting future trends and target setting.

Cardiovascular disease rates are known to increase immediately after a severe earthquake. However, less is known about the magnitude of this increase over time in relation to the amount of housing damage. We assessed the effect of area housing damage from a major earthquake sequence in Christchurch, Canterbury province, New Zealand, on cardiovascular disease-related hospital admissions and deaths. For this cohort-linkage study, we used linked administrative datasets from the Statistics New Zealand Integrated Data Infrastructure to identify individuals aged 45 years or older living in Christchurch from the date of the first earthquake on Sept 4, 2010. Individuals were assigned the average damage level for their residential meshblock (small neighbourhood generally comprising 10-50 dwellings) using the insurance-assessed residential building damage costs obtained from the Earthquake Commission as a proportion of property value. We calculated the rates of cardiovascular disease-related hospital admissions (including myocardial infarction) and cardiovascular disease-related mortality and rate ratios (adjusted for age, sex, ethnicity, small-area deprivation index, and personal income) by level of housing damage in the first year and the 4 subsequent years after the earthquake. The rate ratio association between earthquake housing damage and cardiovascular event was examined by Poisson regression, and linear test of trends across damage categories was done by regression modeling. We identified 179 000 residents living in the earthquake-affected region of Christchurch, of whom 148 000 had complete data. For the first 3 months after the Feb 22, 2011 earthquake, the Poisson regression-adjusted rate ratio (RR) for cardiovascular disease-related hospital admissions for residents from areas that were most damaged (compared with residents from the least damaged areas) was 1·12 (95% CI 0·96-1·32; test for linear trend p=0·239). In the first year after the earthquake sequence, for residents from areas that were most damaged (vs the least damaged areas), Poisson regression-adjusted RRs were 1·10 (1·01-1·21; test for linear trend p=0·068) for cardiovascular disease-related hospital admissions, 1·22 (1·00-1·48; p=0·036) for myocardial infarction-related hospital admissions, and 1·25 (1·06-1·47; p=0·105) for cardiovascular disease-related mortality, corresponding to an excess of 66 (95% CI 7-125) cardiovascular disease-related hospital admissions, including 29 (0-53) additional myocardial infarction-related hospital admissions and 46 (13-73) additional deaths from cardiovascular disease. In the 4 subsequent years, we found no evidence of an association of these outcomes with earthquake damage. Rates of cardiovascular disease and myocardial infarction were increased in people living in areas with more severely damaged homes in the first year after a major earthquake. Policy responses to reduce the effect of earthquake damage on cardiovascular disease could include pre-earthquake measures to minimise building damage, early wellbeing interventions within the first year to address post-earthquake stress, and enhanced provision of cardiovascular disease prevention and treatment services. Healthier Lives National Science Challenge and Natural Hazards Research Platform, Ministry of Business, Innovation and Employment.

Internationally, ethnic inequalities in mortality within countries are increasingly recognized as a public health concern. But few countries have data to monitor such inequalities. We aimed to provide a detailed description of ethnic inequalities (Māori [indigenous], Pacific, and European/Other) in mortality for a country with high quality ethnicity data, using both standard and novel visualization methods. Cohort studies of the entire New Zealand population were conducted, using probabilistically-linked Census and mortality data from 1981 to 2011 (68.9 million person years). Absolute (standardized rate difference) and relative (standardized rate ratio) inequalities were calculated, in 1–74-year-olds, for Māori and Pacific peoples in comparison to European/Other. All-cause mortality rates were highest for Māori, followed by Pacific peoples then European/Other, and declined in all three ethnic groups over time. Pacific peoples experienced the slowest annual percentage fall in mortality rates, then Māori, with European/Other having the highest percentage falls – resulting in widening relative inequalities. Absolute inequalities, however, for both Māori and Pacific males compared to European/Other have been falling since 1996. But for females, only Māori absolute inequalities (compared with European/Other) have been falling. Regarding cause of death, cancer is becoming a more important contributor than cardiovascular disease (CVD) to absolute inequalities, especially for Māori females. We found declines in all-cause mortality rates, over time, for each ethnic group of interest. Ethnic mortality inequalities are generally stable or even falling in absolute terms, but have increased on a relative scale. The drivers of these inequalities in mortality are transitioning over time, away from CVD to cancer and diabetes; such transitions are likely in other countries, and warrant further research. To address these inequalities, policymakers need to enhance prevention activities and health care delivery, but also support wider improvements in educational achievement and socioeconomic position for highest need populations.