Assessing the causal relationship between income inequality and mortality and self-rated health: protocol for systematic review and meta-analysis

Global Burden of Cardiovascular Disease Attributable to Sugar-Sweetened Beverages in Middle-Aged Adults: An Age-Period-Cohort Modelling Study

BACKGROUND

Cardiovascular disease (CVD) presents a significant burden among middle-aged adults (aged 35-64). Diet high in sugar-sweetened beverages is a notable CVD risk factor.

METHODS

Using Global Burden of Disease data from 1990 to 2019, age-standardized rates (ASRs) and average annual percentage change of ASRs were used to describe this burden and its changing trend.

RESULTS

In 2019, global CVD-related ASR (per 100 000) of deaths attributable to sugar-sweetened beverages in middle-aged adults reached 1.91 (95% uncertainty interval [UI], 1.07-2.63) compared with 2.75 (95% UI, 1.76-3.59) in 1990. The global ASR of disability-adjusted life years (DALYs) reached 69.71 in 2019 (95% UI, 38.38-96.36) compared with 97.98 (95% UI, 62.29-128.39) in 1990. Men had more than twice the deaths and DALYs as women. Low and low-middle sociodemographic index regions exhibited a higher burden of DALYs and deaths. In 2019, India and China had the highest numbers of deaths and DALYs and the Solomon Islands and Afghanistan recorded the highest ASRs of deaths and DALYs. A negative linear correlation was observed between sociodemographic index and ASRs of deaths (R=-0.10, P=0.010) and DALYs (R=-0.09, P=0.031) across 21 Global Burden of Disease regions. An inequalities analysis indicated that DALYs due to CVD were disproportionately higher in countries with lower sociodemographic index in 2019 (concentration index of inequality=-0.05 [95% CI, -0.1 to -0.01]).

CONCLUSIONS

Globally, sugar-sweetened beverages have contributed to a substantial increase in DALYs and deaths related to CVD in middle-aged adults over the past 30 years, especially among men and in low sociodemographic index countries.

Applying Bradford Hill to assessing causality in systematic reviews: A transparent approach using process tracing

BACKGROUND

Bradford Hill (BH) viewpoints are widely used to assess causality in systematic reviews, but their application has often lacked reproducibility. We describe an approach for assessing causality within systematic reviews ('causal' reviews), illustrating its application to the topic of income inequality and health. Our approach draws on principles of process tracing, a method used for case study research, to harness BH viewpoints to judge evidence for causal claims.

METHODS

In process tracing, a hypothesis may be confirmed by observing highly unique evidence and disconfirmed by observing highly definitive evidence. We drew on these principles to consider the value of finding supportive or contradictory evidence for each BH viewpoint characterised by its uniqueness and definitiveness.

RESULTS

In our exemplar systematic review, we hypothesised that income inequality adversely affects self-rated health and all-cause mortality. BH viewpoints 'analogy' and 'coherence' were excluded from the causal assessment because of their low uniqueness and low definitiveness. The 'experiment' viewpoint was considered highly unique and highly definitive, and thus could be particularly valuable. We propose five steps for using BH viewpoints in a 'causal' review: (1) define the hypothesis; (2) characterise each viewpoint; (3) specify the evidence expected for each BH viewpoint for a true or untrue hypothesis; (4) gather evidence for each viewpoint (e.g., systematic review meta-analyses, critical appraisal, background knowledge); (5) consider if each viewpoint was met (supportive evidence) or unmet (contradictory evidence).

CONCLUSIONS

Incorporating process tracing has the potential to provide transparency and structure when using BH viewpoints in 'causal' reviews.

What is the relationship between changes in the size of economies and mortality derived population health measures in high income countries: A causal systematic review

CONTEXT

The economy has been long recognised as an important determinant of population health and a healthy population is considered important for economic prosperity.

AIM

To systematically review the evidence for a causal bidirectional relationship between aggregate economic activity (AEA) at national level for High Income Countries, and 1) population health (using mortality and life expectancy rates as indicators) and 2) inequalities in population health.

METHODS

We undertook a systematic review of quantitative studies considering the relationship between AEA (GDP, GNI, GNP or recession) and population health (mortality or life expectancy) and inequalities for High Income Countries. We searched eight databases and grey literature. Study quality was assessed using an adapted version of the Effective Public Health Practice Project's Quality Assessment tool. We used Gordis' adaptation of the Bradford-Hill framework to assess causality. The studies were synthesised using Cochrane recommended alternative methods to meta-analysis and reported following the Synthesis without Meta-analysis (SWiM) guidelines. We assessed the certainty of the evidence base in line with GRADE principles.

FINDINGS

Of 21,099 records screened, 51 articles were included in our analysis. There was no evidence for a consistent causal relationship (either beneficial or harmful) of changes in AEA leading to changes in population health (as indicated by mortality or life expectancy). There was evidence suggesting that better population health is causally related to greater AEA, but with low certainty. There was insufficient evidence to consider the causal impact of AEA on health inequalities or vice versa.

CONCLUSIONS

Changes in AEA in High Income Countries did not have a consistently beneficial or harmful causal relationship with health, suggesting that impacts observed may be contextually contingent. We tentatively suggest that improving population health might be important for economic prosperity. Whether or not AEA and health inequalities are causally linked is yet to be established.

Causal Assessment of Income Inequality on Self-Rated Health and All-Cause Mortality: A Systematic Review and Meta-Analysis

Policy Points Income is thought to impact a broad range of health outcomes. However, whether income inequality (how unequal the distribution of income is in a population) has an additional impact on health is extensively debated. Studies that use multilevel data, which have recently increased in popularity, are necessary to separate the contextual effects of income inequality on health from the effects of individual income on health. Our systematic review found only small associations between income inequality and poor self-rated health and all-cause mortality. The available evidence does not suggest causality, although it remains methodologically flawed and limited, with very few studies using natural experimental approaches or examining income inequality at the national level.

CONTEXT

Whether income inequality has a direct effect on health or is only associated because of the effect of individual income has long been debated. We aimed to understand the association between income inequality and self-rated health (SRH) and all-cause mortality (mortality) and assess if these relationships are likely to be causal.

METHODS

We searched Medline, ISI Web of Science, Embase, and EconLit (PROSPERO: CRD42021252791) for studies considering income inequality and SRH or mortality using multilevel data and adjusting for individual-level socioeconomic position. We calculated pooled odds ratios (ORs) for poor SRH and relative risk ratios (RRs) for mortality from random-effects meta-analyses. We critically appraised included studies using the Risk of Bias in Nonrandomized Studies - of Interventions tool. We assessed certainty of evidence using the Grading of Recommendations Assessment, Development and Evaluation framework and causality using Bradford Hill (BH) viewpoints.

FINDINGS

The primary meta-analyses included 2,916,576 participants in 38 cross-sectional studies assessing SRH and 10,727,470 participants in 14 cohort studies of mortality. Per 0.05-unit increase in the Gini coefficient, a measure of income inequality, the ORs and RRs (95% confidence intervals) for SRH and mortality were 1.06 (1.03-1.08) and 1.02 (1.00-1.04), respectively. A total of 63.2% of SRH and 50.0% of mortality studies were at serious risk of bias (RoB), resulting in very low and low certainty ratings, respectively. For SRH and mortality, we did not identify relevant evidence to assess the specificity or, for SRH only, the experiment BH viewpoints; evidence for strength of association and dose-response gradient was inconclusive because of the high RoB; we found evidence in support of temporality and plausibility.

CONCLUSIONS

Increased income inequality is only marginally associated with SRH and mortality, but the current evidence base is too methodologically limited to support a causal relationship. To address the gaps we identified, future research should focus on income inequality measured at the national level and addressing confounding with natural experiment approaches.

Healthcare costs attributable to abnormal weight in China: evidence based on a longitudinal study

BACKGROUND

The prevalence of abnormal weight is on the rise, presenting serious health risks and socioeconomic problems. Nonetheless, there is a lack of studies on the medical cost savings that can be attained through the mitigation of abnormal weight. The aim of this study was to estimate the impact of abnormal weight on healthcare costs in China.

METHODS

The study employed a 4-wave panel data from China Family Panel Studies (CFPS) between 2012 and 2018 (11,209 participants in each wave). Inpatient, non-inpatient and total healthcare costs were outcome variables. Abnormal weight is categorized based on body mass index (BMI). Initially, the two-part model was employed to investigate the impact of overweight/obesity and underweight on healthcare utilisation and costs, respectively. Subsequently, the estimated results were utilised to calculate the overweight/obesity attributable fraction (OAF) and the underweight attributable fraction (UAF).

RESULTS

In 2018, healthcare costs per person for overweight and obese population were estimated to be $607.51 and $639.28, respectively, and the underweight population was $755.55. In comparison to people of normal weight, individuals who were overweight/obese (OR = 1.067, p < 0.05) was more likely to utilise healthcare services. Overweight/obesity attributable fraction (OAF) was 3.90% of total healthcare costs and 4.31% of non-inpatient costs. Overweight/obesity does not result in additional healthcare expenditures for young people but increases healthcare costs for middle-aged adults (OAF = 7.28%) and older adults (OAF = 6.48%). The non-inpatient cost of underweight population was significantly higher than that of normal weight population (β = 0.060,p < 0.1), but the non-inpatient health service utilisation was not significantly affected.

CONCLUSIONS

Abnormal weight imposes a huge economic burden on individuals, households and the society. Abnormal weight in Chinese adults significantly increased healthcare utilisation and costs, particular in non-inpatient care. It is recommended that government and relevant social agencies provide a better social environment to enhance individual self-perception and promote healthy weight.