Investigating change across time in prevalence or association using observational data: guidance on utility, methodology, and interpretation

Across the health and social sciences, addressing many key scientific or policy questions requires an understanding of whether a given quantity has changed over time—e.g., by year of data collection or by birth year. For example, has the occurrence of—or socioeconomic inequity in—a given health outcome changed across time? Or has social mobility improved or worsened in recently born generations? Understanding such issues motivates and informs future policy development, and can provide clues to aetiology by contrasting with changes in purported determinants or confounding factors. Accordingly, comparative or cross-cohort research initiatives are increasingly prominent components of health and social sciences yet, to our knowledge, no structured guidance exists to inform the implementation or appraisal of such studies. We thus collate relevant learning and produce guidance, focusing on changes across time in 1) outcome occurrence or levels for continuous outcomes; and 2) the magnitude and/or direction of associations. We discuss their use and importance (when does such comparative research add value?), study inclusion (which studies could be used?), sources of bias (what can go wrong and how can biases be mitigated?), and interpretation (how can between study differences be explained?). We provide a checklist to structure such guidance which applies to multiple study designs (e.g., cohort or repeated cross-sectional studies) and may be a useful tool for future authors and reviewers focusing on comparative research across time, cohort or indeed place. Finally, we provide analytical syntax and tutorial content with example data to facilitate future analysis and data visualisation (see https://osf.io/d569x/).

Exploring Pathways of Socioeconomic Inequity in Vegetable Expenditure Among Consumers Participating in a Grocery Loyalty Program in Quebec, Canada, 2015–2017

Vegetable consumption remains consistently low despite supportive policy and investments across the world. Vegetables are available in great variety, ranging in their processing level, availability, cost, and arguably, nutritional value. A retrospective longitudinal study was conducted in Quebec, Canada to explore pathways of socioeconomic inequity in vegetable expenditure. Data was obtained for consumers who participated in a grocery loyalty program from 2015 to 2017 and linked to the 2016 Canadian census. Vegetable expenditure share (%) was examined as a fraction of the overall food basket and segmented by processing level. Panel random effects and tobit models were used overall and to estimate the stratified analysis by median income split. Consumers allocated 8.35% of their total food expenditure to vegetables, which was mostly allocated to non-processed fresh (6.88%). Vegetable expenditure share was the highest in early winter and lowest in late summer. In the stratified analysis, the low-income group exhibited less seasonal variation, allocated less to fresh vegetables, and spent more on canned and frozen compared to the high-income group. Measures of socioeconomic status were all significant drivers of overall vegetable consumption. Consumers with high post-secondary education in the low-income group spent 2% more on vegetables than those with low education. The complexity of observed expenditure patterns points to a need for more specific vegetable consumption guidelines that include provisions by processing level. Implications for education, marketing, intersectional policies, and the role of government are discussed. Governments can scale present efforts and catalyze health-promoting investments across local, state, national, and global food systems.

Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies

Objective To examine whether overall lifestyles mediate associations of socioeconomic status (SES) with mortality and incident cardiovascular disease (CVD) and the extent of interaction or joint relations of lifestyles and SES with health outcomes. Design Population based cohort study. Setting US National Health and Nutrition Examination Survey (US NHANES, 1988-94 and 1999-2014) and UK Biobank. Participants 44 462 US adults aged 20 years or older and 399 537 UK adults aged 37-73 years. Exposures SES was derived by latent class analysis using family income, occupation or employment status, education level, and health insurance (US NHANES only), and three levels (low, medium, and high) were defined according to item response probabilities. A healthy lifestyle score was constructed using information on never smoking, no heavy alcohol consumption (women ≤1 drink/day; men ≤2 drinks/day; one drink contains 14 g of ethanol in the US and 8 g in the UK), top third of physical activity, and higher dietary quality. Main outcome measures All cause mortality was the primary outcome in both studies, and CVD mortality and morbidity in UK Biobank, which were obtained through linkage to registries. Results US NHANES documented 8906 deaths over a mean follow-up of 11.2 years, and UK Biobank documented 22 309 deaths and 6903 incident CVD cases over a mean follow-up of 8.8-11.0 years. Among adults of low SES, age adjusted risk of death was 22.5 (95% confidence interval 21.7 to 23.3) and 7.4 (7.3 to 7.6) per 1000 person years in US NHANES and UK Biobank, respectively, and age adjusted risk of CVD was 2.5 (2.4 to 2.6) per 1000 person years in UK Biobank. The corresponding risks among adults of high SES were 11.4 (10.6 to 12.1), 3.3 (3.1 to 3.5), and 1.4 (1.3 to 1.5) per 1000 person years. Compared with adults of high SES, those of low SES had higher risks of all cause mortality (hazard ratio 2.13, 95% confidence interval 1.90 to 2.38 in US NHANES; 1.96, 1.87 to 2.06 in UK Biobank), CVD mortality (2.25, 2.00 to 2.53), and incident CVD (1.65, 1.52 to 1.79) in UK Biobank, and the proportions mediated by lifestyle were 12.3% (10.7% to 13.9%), 4.0% (3.5% to 4.4%), 3.0% (2.5% to 3.6%), and 3.7% (3.1% to 4.5%), respectively. No significant interaction was observed between lifestyle and SES in US NHANES, whereas associations between lifestyle and outcomes were stronger among those of low SES in UK Biobank. Compared with adults of high SES and three or four healthy lifestyle factors, those with low SES and no or one healthy lifestyle factor had higher risks of all cause mortality (3.53, 3.01 to 4.14 in US NHANES; 2.65, 2.39 to 2.94 in UK Biobank), CVD mortality (2.65, 2.09 to 3.38), and incident CVD (2.09, 1.78 to 2.46) in UK Biobank. Conclusions Unhealthy lifestyles mediated a small proportion of the socioeconomic inequity in health in both US and UK adults; therefore, healthy lifestyle promotion alone might not substantially reduce the socioeconomic inequity in health, and other measures tackling social determinants of health are warranted. Nevertheless, healthy lifestyles were associated with lower mortality and CVD risk in different SES subgroups, supporting an important role of healthy lifestyles in reducing disease burden.

Correlation of mesolevel characteristics of the healthcare system and socioeconomic inequality in healthcare use: a scoping review protocol

IntroductionAlthough the impact of macrolevel characteristics of health systems on socioeconomic inequity in health has been studied extensively, the impact of access characteristics on a smaller scale of health systems has received less attention. These mesolevel characteristics can influence access to healthcare and might have the potential to moderate or aggravate socioeconomic inequity in healthcare use. This scoping review aims to map the existing evidence of the association of socioeconomic inequity in healthcare use and mesolevel access characteristics of the health system.Methods and analysisIn conducting the scoping review, we follow the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols Extension for Scoping Reviews. The search will be carried out in four scientific databases: MEDLINE (via PubMed), Web of Science, Scopus and PsycINFO. Main eligibility criteria are inclusion in the analysis of a measure of socioeconomic position, a measure of individual healthcare use and a mesolevel determinant of access to healthcare services. The selection process consists of two consecutive screening stages (first: title/abstract; second: full text). At both stages, two reviewers independently assess the eligibility of studies. In case of disagreement, a third reviewer will be involved. Cohen’s kappa will be calculated to report inter-rater agreement between reviewers. Results are synthesised narratively, as a high heterogeneity of studies is expected.Ethics and disseminationNo primary data are collected for the presented scoping review. Therefore, ethical approval is not necessary. The scoping review will be published in an international peer-reviewed journal, and findings will be presented on national and international conferences.

The absolute socioeconomic inequity attributable to smoking

Background: Smoking has several consequences over the society and the economy at same time. Because of smoking smokers are reducing the life quality and life expectation too. That is the main cause of absolute socioeconomic inequity attributable to smoking. Objective: To characterize the absolute socioeconomic inequity attributable to smoking. Materials and methods: Were used several theorical methods as the inductive – deductive and the comparative too. As empirical method was used the bibliographic research. Results: Smoking is the main cause of the existence of this particular inequity form. That’s why to eliminate the absolute socioeconomic inequity attributable to smoking is necessary focus the attention in the reduction of the tobacco consumption intensity as main explicative variable for personal smoker demand of health services because of smoking. Conclusions: The absolute socioeconomic inequity attributable to smoking is showed by mortality and morbidity too. In both case the strategic to reduce the tobacco consumption must focus the attention as main way to control, reduce and eliminate the absolute socioeconomic inequity attributable to smoking

University of Medical Science of Havana Faculty of Medical Science “10 de Octubre” Diploma course: The socioeconomic inequity attributable to smoking

Background: Socioeconomic inequity attributable to smoking has several social costs moreover than the disparities caused by the inequity cause. The precise understanding about the socioeconomic inequity attributable to smoking will contribute to a better judgment about the smoking impact over the society. That’s why the close mutual relation between Public Health, Superior Education, Economy and other social sector may make significant intake to the specialized professional formation for the smoking control. Objective: To design a diploma course about the socioeconomic inequity attributable to smoking. Materials and methods: As teoricals methods were utilized the analysis and synthesis, the comparative and the inductive deductive. As empiric method was used the bibliographic research. Results: Related to the socioeconomic inequity attributable to smoking is important to know and to understand what is, how impact over the society, how to measure it and what to do for a better control. All these questions are analyzed and answered in this diploma course. Conclusion: The diploma course takes account the particularities from several social sectors respect to the postgraduate education necessities about the smoking economic control specifically in references to the socioeconomic inequity attributable to smoking.

Fairness-Aware Demand Prediction for New Mobility

Emerging transportation modes, including car-sharing, bike-sharing, and ride-hailing, are transforming urban mobility yet have been shown to reinforce socioeconomic inequity. These services rely on accurate demand prediction, but the demand data on which these models are trained reflect biases around demographics, socioeconomic conditions, and entrenched geographic patterns. To address these biases and improve fairness, we present FairST, a fairness-aware demand prediction model for spatiotemporal urban applications, with emphasis on new mobility. We use 1D (time-varying, space-constant), 2D (space-varying, time-constant) and 3D (both time- and space-varying) convolutional branches to integrate heterogeneous features, while including fairness metrics as a form of regularization to improve equity across demographic groups. We propose two spatiotemporal fairness metrics, region-based fairness gap (RFG), applicable when demographic information is provided as a constant for a region, and individual-based fairness gap (IFG), applicable when a continuous distribution of demographic information is available. Experimental results on bike share and ride share datasets show that FairST can reduce inequity in demand prediction for multiple sensitive attributes (i.e. race, age, and education level), while achieving better accuracy than even state-of-the-art fairness-oblivious methods.

Rates to Measures the Social Inequity Attributable To Smoking

Introduction: Smoking has two main explicative variables given by the consumption of tobacco and cigarettes and the smokers’ number. The relation between both and the researched risk factor determine the social behavior of it. The social inequity attributable to smoking is given by the particular way to impact over the researched population. Objective: To design an inequity rate for each identified form of social inequity attributable to smoking. Was made an analytic research about the smoking social inequity. Materials and Methods: Were used like theorical methods the comparative and the inductive deductive and like empiric method the bibliographic research. Results: The social inequity attributable to smoking is given by the social cost because of smoking. These costs are determined by the smoking effect over the economic resources consumption´s financing the health services and the smoking effect over the society and the economy in general by the labor productivity lose. Conclusion: Smoking like risk factor has several forms to impact over the population researched. Each identified form of social inequity has one particular form of social inequity and one form of socioeconomic inequity too.