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Reporting of equity in observational epidemiology: A methodological review

Omar Dewidar1,2, Ali Al-Zubaidi2,3, Mostafa Bondok2,4, Leenah Abdelrazeq2, Jimmy Huang2, Alyssa Jearvis2, Lucy C Barker5,6, Nour Elmestekawy2,7, Elizabeth Goghomu2, Tamara Rader8, Janice Tufte9, Regina Greer-Smith10, Hugh S Waddington11,12, Stuart G Nicholls13,14, Julian Little15, Billie-Jo Hardy16,17, Tanya Horsley18, Taryn Young19, Luis Gabriel Cuervo20,21, Melissa K Sharp22, Catherine Chamberlain23,24, Beverley Shea13,15, Peter Craig25, Daeria O Lawson26, Anita Rizvi27, Charles S Wiysonge28, Tamara Kredo28,29, Damian Francis30, Elizabeth Kristjansson13,15, Zulfiqar Bhutta31,32, Alba Antequera33, GJ Melendez-Torres34, Tomas Pantoja35, Xiaoqin Wang36, Janet Jull37, Janet Hatcher Roberts38, Sarah Funnell39, Howard White40, Alison Krentel2, Michael Johnson Mahande41, Jacqueline Ramke42, George Wells15,43, Jennifer Petkovic2, Kevin Pottie44,45, Loveline Niba46,47, Cindy Feng15, Miriam N Nguliefem15, Peter Tugwell2,13,48, Lawrence Mbuagbaw26*, Vivian Welch2,15*

1 Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
2 Bruyère Research Institute, University of Ottawa, Ottawa, Ontario, Canada
3 School of Medicine, University College Cork, Cork, Ireland
4 Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
5 Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
6 Women’s College Hospital, Toronto, Ontario, Canada
7 Faculty of Social Sciences, University of Ottawa, Ottawa, Ontario, Canada
8 Freelance health research librarian, Ottawa, Ontario, Canada
9 Hassanah Consulting, Seattle, Washington State, USA
10 Healthcare Research Associates, LLC/S.T.A.R. Initiative, California, USA
11 London School of Hygiene and Tropical Medicine, London, UK
12 London International Development Centre, London, UK
13 Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
14 Office for Patient Engagement in Research Activity (OPERA), Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
15 School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
16 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
17 Well Living House, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada
18 Royal College of Physicians and Surgeons of Canada, Ottawa, Ontario, Canada
19 Centre for Evidence Based Health Care, Department of Global Health, Stellenbosch University, Stellenbosch, South Africa
20 Department of Evidence and Intelligence for Action in Health, Pan American Health Organization (PAHO/WHO), Washington, DC, USA
21 Doctoral Programme on Methodology of Biomedical Research and Public Health, Universitat Autònoma de Barcelona, Barcelona, Spain
22 Department of Public Health and Epidemiology, RCSI University of Medicine and Health Sciences, Dublin, Ireland
23 Judith Lumley Centre, School of Nursing and Midwifery, La Trobe University, Melbourne, Australia
24 Ngangk Yira Research Centre for Aboriginal Health and Social Equity, Murdoch University, Perth, Australia
25 Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
26 Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
27 School of Psychology, University of Ottawa, Ottawa, Ontario, Canada
28 Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa
29 Centre for Evidence Based Health Care, Department of Global Health, Stellenbosch University, Stellenbosch, South Africa
30 School of Health and Human Performance, Georgia College, Milledgeville, Georgia, USA
31 Centre for Global Child Health, Hospital for Sick Children, Toronto, Canada
32 Institute for Global Health and Development, Aga Khan University, Karachi, Pakistan
33 Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
34 Department of Public Health and Sports Science, University of Exeter College of Medicine and Health, Exeter, UK
35 Family Medicine Department, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile
36 Michael G. DeGroote Institute for Pain Research and Care, McMaster University, Hamilton, Canada
37 Faculty of Health Sciences, School of Rehabilitation Therapy, Queen’s University, Kingston, Canada
38 World Health Organization Collaborating Centre for Knowledge Translation and Health Technology Assessment in Health Equity, Ottawa, Canada
39 Department of Family Medicine, Faculty of Health Sciences, Queen’s University, Kingston, Ontario
40 Campbell Collaboration, Oslo, Norway
41 Department of Epidemiology and Biostatistics, Kilimanjaro Christian Medical University College, Tanzania.
42 International Centre for Eye Health, London School of Hygiene and Tropical Medicine, London, UK
43 University of Ottawa Heart Institute, Ottawa, Canada
44 C.T. Lamont Primary Care Research Centre, Bruyère Research Institute, Ottawa, Canada
45 Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Canada
46 Department of Public Health, The University of Bamenda, Bamenda, Cameroon
47 Nutrition and Health Research Group (NHRG), Bamenda, Cameroon
48 Faculty of Medicine, University of Ottawa, Ottawa, Canada
* Joint senior authorship.

DOI: 10.7189/jogh.14.04046




Observational studies can inform how we understand and address persisting health inequities through the collection, reporting and analysis of health equity factors. However, the extent to which the analysis and reporting of equity-relevant aspects in observational research are generally unknown. Thus, we aimed to systematically evaluate how equity-relevant observational studies reported equity considerations in the study design and analyses.


We searched MEDLINE for health equity-relevant observational studies from January 2020 to March 2022, resulting in 16 828 articles. We randomly selected 320 studies, ensuring a balance in focus on populations experiencing inequities, country income settings, and coronavirus disease 2019 (COVID-19) topic. We extracted information on study design and analysis methods.


The bulk of the studies were conducted in North America (n = 95, 30%), followed by Europe and Central Asia (n = 55, 17%). Half of the studies (n = 171, 53%) addressed general health and well-being, while 49 (15%) focused on mental health conditions. Two-thirds of the studies (n = 220, 69%) were cross-sectional. Eight (3%) engaged with populations experiencing inequities, while 22 (29%) adapted recruitment methods to reach these populations. Further, 67 studies (21%) examined interaction effects primarily related to race or ethnicity (48%). Two-thirds of the studies (72%) adjusted for characteristics associated with inequities, and 18 studies (6%) used flow diagrams to depict how populations experiencing inequities progressed throughout the studies.


Despite over 80% of the equity-focused observational studies providing a rationale for a focus on health equity, reporting of study design features relevant to health equity ranged from 0–95%, with over half of the items reported by less than one-quarter of studies. This methodological study is a baseline assessment to inform the development of an equity-focussed reporting guideline for observational studies as an extension of the well-known Strengthening Reporting of Observational Studies in Epidemiology (STROBE) guideline.

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Wilson and colleagues emphasise that ‘We have to acknowledge that as researchers we have power. We have to use our power and knowledge responsibly. We have to act. That might be acting to resolve difference or acting to ensure accuracy or acting by refusing to follow the status quo. It requires us to use our power as researchers to change ourselves as individuals, but also all of humankind.’ [1].

Health inequities are unfair and unjust inequalities in health that stem from various social determinants of health (e.g. gender, socioeconomic status, and ethnicity, primarily due to structural racism and systems of oppression [2,3]. Addressing these inequities can promote well-being between and within populations [4]. These social determinants of health have been summarised by several frameworks [57], including the PROGRESS-Plus framework that outlines factors stratifying opportunities for health. The mnemonic stands for Place of residence, Race/ethnicity/culture/language, Occupation/out of work, Gender/sex, Religion, Education, Socioeconomic status, and Social capital [8]. Additional factors are recognised in the ‘Plus’ component such as individual characteristics (age, disability), features of relationships (e.g. smoking parents), and time-dependent transitions (temporary health disadvantages) [8].

Despite global commitments to address inequities, there remains a need for more empirical research to identify and understand the complex underlying structures of inequities [9]. The lack of rigour in the collection of health equity data hampers the development of health-equitable programs and policies for better overall health. Many authors have urged researchers to prioritise health equity research in policy, health systems, and health services (including organisation, delivery, prioritisation, and implementation), integrating it into primary and secondary research [1013].

The experiences of health policies, systems, and services by populations experiencing inequities can be captured well in descriptive or analytical research that evaluates a question without intervention [14,15]. This type of research is conducted by means of observational studies, which tend to predominate in health-related research [16]; they can be used to investigate causal relationships in the presence of a control group [17] and provide valuable knowledge to inform health guidelines and policy decisions. For instance, observational research conducted during the coronavirus disease 2019 (COVID-19) pandemic highlighted the vast inequities in society and informed public health responses to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1820].

To improve evidence to inform equity decisions, comprehensive reporting (credible and transparent) of equity-related aspects in research is essential in assessing the reliability, reproducibility, and methodological rigour of studies and enhancing the social value and accountability of the research [21––23]. Reporting guidelines can contribute to meeting these goals by increasing the completeness and transparency of research papers [2124]. The Strengthening of the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline is a well-known tool for enhancing the reporting of observational research. While surveys have found high levels of authors who self-reported the use of the STROBE guideline (over 60% of observational study authors) [25], and the guidelines are mandated or endorsed by many journals, the current guidelines do not include guidance for consideration of equity. Indeed, analyses of observational studies have found a persistent lack of integration and reporting of sex and gender in these studies [2628], potentially explained by a lack of guidance on how to report equity in these studies.

Given that it is not yet standard practice to apply and use an equity lens in reporting observational health research, we intend to extend the STROBE guidelines to assist in reporting equity. As a part of that objective, we evaluated how equity-relevant observational studies describe the characteristics of their samples, design features and analysis, and interpretation of their findings across PROGRESS-Plus factors.


This methodological review is part of a larger project aimed to develop reporting guidelines for equity in observational studies [29]. It follows the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-Equity), PRISMA 2020, and Guidance for Reporting Involvement of Patients and the Public [12,30,31] (Tables S1–3 the Online Supplementary Document). The protocol for this review has been previously published [32].

Patient and public engagement

JT and GSR are part of our patient and public advisory board for the development of the STROBE-Equity guidelines. These team members experience inequities and have experience with participating in health equity research. They were recruited by nomination or involvement in previous groups. The patient and public partners were involved in discussions identifying the need for the development of the guidelines. They were involved in refining the STROBE-Equity checklist by identifying areas where they believed equity should be addressed. The patient and public partners were also involved in the design of this methodological assessment and discussions related to highlighting the primary findings. The patient and public partners were regularly updated on this project’s progress through quarterly technical advisory meetings and patient steering committee meetings. The study updates were presented at the meetings and shared through newsletters. Although we shared early iterations of the manuscript with the patient and public partners simultaneously with the researchers via email, we found that this process was not optimal. The methodological comments over-clouded the critical comments and reflections of the patient partners, and this impaired their ability to provide feedback. Therefore, we sent the last iteration to the patient advisors separately, with a separate deadline for turnaround. We found this resulted in better engagement by focusing feedback on which findings were important to populations experiencing inequities and the terminologies used to refer to populations throughout the manuscript.

Search strategy

An information specialist (TR) developed and peer-reviewed the search strategy using the Peer Review of Electronic Search Strategies guideline [33]. We searched Ovid MEDLINE from January 2020 to March 2022 using a validated search filter for health equity studies [34]. We chose this period because we anticipated a focus on health equity due to the pandemic. We enhanced the filter for observational studies by adding two terms to identify cross-sectional studies [35]. Additional terms such as ‘instrumental variable’, ‘discontinuity design’, ‘interrupted time series’, ‘discontinuity design’, ‘matching’, ‘synthetic control’, and ‘difference-in-difference’ were included to capture observational econometric studies (Online Supplementary Document). Review articles and randomised controlled trials were excluded using validated study design filters [36].

Eligibility criteria

Following our study protocol [32], we purposefully randomly selected 320 health equity-relevant observational studies using Jull and colleagues framework [37] using a three-factor randomised sampling approach to achieve balance across: country income settings; whether or not the study related to COVID-19, and whether the study focusing on population(s) experiencing inequalities.

Detailed explanations of purposive random sampling, sample size determination, and definitions of key terms (context, health equity, health equity-relevant studies and observational studies) can be found in the published protocol [32] and Online Supplementary Document.

Screening and data extraction

We placed the retrieved articles in random order using the DistillerSR, version 2.35 (DistillerSR Inc., Ottawa, Canada) random order generator feature, and we then systematically screened articles in order until we had included the pre-specified number of 320 articles. At the title and abstract stage, studies were screened by one of the project team members (AA, MB, LA, JH, AJ, OD) [38]. Full texts were screened by an investigator within that group (AA, MB, LA, JH, AJ), and researcher OD validated all screening decisions. Conflicts during full-text screening were resolved through discussions among the team members during weekly meetings. We developed and pre-tested a data extraction form using DistillerSR software, which was used to capture study characteristics, including the conditions assessed [39], exposures [40], country, conflict of interest, funding and use of a reporting guideline. A data dictionary was developed and refined through pre-testing to ensure consistent information extraction (Online Supplementary Document). We assessed the reporting of health equity considerations across PROGRESS-Plus factors and contextual factors across the whole study using our draft STROBE-Equity checklist [29], including the abstract, background and rationale, population characteristics, results, interpretation of applicability, and discussion).

We analysed the descriptive characteristics of all the included studies using frequencies and percentages. Each equity reporting item was reported as count and percentages with 95% confidence intervals (CIs). We report our findings according to study design elements, analyses, and completeness of reporting. All analyses were conducted using Stata, version 18 (StataCorp LLC, College Station, TX, USA).


Search results

Our search yielded 16 828 articles. After removing duplicates, 15 412 article references remained for the title and abstract screening. A total of 4021 studies were reviewed according to our eligibility criteria to attain our intended sample size of 320 eligible studies (Figure 1).

Figure 1.  Study flow diagram.

Characteristics of included studies

Approximately two-thirds of studies (n = 220, 69%) had a cross-sectional design. Half (n = 171, 53%) addressed general health and well-being, while 49 (15%) focused on mental health conditions. In terms of geographical distribution, about one-third (n = 95, 30%) were conducted in North America, 55 (17%) in Europe and Central Asia, 51 (16%) in East Asia and Pacific Asia, and 34 (11%) in South Asia. Further, 128 studies (40%) lacked a specific exposure variable, whereas 121 (38%) assessed health outcomes in relation to specific individual characteristics and behaviours (such as age or ethnicity). Funding for half of the studies (n = 150, 48%) came from governments or not-for-profit organisations. Only 17 studies (5%) reported using the STROBE reporting guidelines for reporting (Table 1). The reporting of each STROBE-Equity candidate item as per the drafted STROBE-Equity checklist is presented in Table S7 in the Online Supplementary Document.

Table 1.  Characteristics of included studies (n = 320)

WordPress Data Table

Reporting of health equity considerations in study design aspects

Few studies (n = 10, 3%) involved patients, community members or interested groups (also known as stakeholders) in formulating research questions and study design, and none of them provided details on how these partnerships were established or managed during the study (Figure 2). A small proportion of the included studies (n = 24, 8%) outlined an informed consent procedure for communities experiencing inequities.

Figure 2.  The reporting of equity in equity-relevant observational studies.

Additionally, about a quarter of the studies (n = 75, 23%) actively recruited participants, with 22 studies (29%) adapting their recruitment methods to reach specific populations defined by PROGRESS-Plus factors. Roughly half of the studies (n = 164, 51%) outlined inclusion or exclusion criteria based on at least one PROGRESS-Plus factor. A minority of the studies (n = 16, 5%) reported efforts to reduce selection bias for populations experiencing inequities, such as using separate inclusion criteria (e.g. cut-offs for clinical indicators) by sex or gender. A subset of the studies (n = 48, 15%) provided contextual information regarding health equity. Further, 10 studies (3%) matched participants across baseline characteristics, four (40%) of which matched participants by at least one PROGRESS-Plus factor. These matching factors were identified by examining the data sets for significant differences across outcomes of interest. A minority of the studies (n = 53, 17%) explained how they determined the relevance of the outcomes to populations experiencing inequities. In 22 studies (7%), authors considered at least one PROGRESS-Plus factor in the sample size calculation.

Three-quarters of the studies (n = 242, 76%) described how the authors of the observational studies obtained information on participant characteristics. The most commonly (n = 85, 35%) collected characteristics using surveys, followed by hospital or tertiary centre databases (n = 80, 33%). Further, 35 studies (14%) relied on self-reporting or self-selection. In 21 studies (9%), participant characteristics were obtained from electronic health records such as Medicare in the USA and the National Health Service in the UK, while another 21 studies (9%) used investigator-observed approaches such as interviews.

The denominator for adapting recruitment methods to recruit populations experiencing inequities is lower than the total number of studies as it represents the number of studies that used active recruitment. The same applies to the denominator for matching across equity factors and adjusting for estimates.

Reporting health equity considerations in analyses

Three-quarters of the studies (n = 233, 73%) examined adjusted associations with health outcomes for at least one PROGRESS-Plus factor. The characteristics analysed varied, with age (n = 164, 70%) and sex (n = 159, 68%) being the most studied factors (Figure 3). Conversely, factors like sexual orientation, pregnancy or breastfeeding and diseases linked to discrimination (e.g. HIV) were analysed in only two studies each (1%). Almost all studies (n = 219, 94%) found statistically significant differences in at least one of the analysed PROGRESS-Plus factors.

Figure 3.  Distribution of analyses in 320 equity relevant-observational studies across PROGRESS-Plus characteristics.

71% of studies (n = 227) conducted additional analyses by including subgroup analyses or effect modification. Among the included studies, 65% (n = 208) reported subgroup analyses involving at least one PROGRESS-Plus factor. The most used subgroup analysis categories were sex (n = 133, 64%), age (n = 112, 54%), and race or ethnicity (n = 83, 40%). No studies conducted subgroup analyses based on social capital, and analyses involving other additional (Plus) characteristics were reported in less than 5% of the studies.

Moreover, 67 studies (21%) incorporated at least one PROGRESS-Plus factor as an effect modifier. Among these, 63 (20%) conducted effect modification assessments using stratified modelling analysis, which involves stratifying the sample by an independent variable and running a model on each stratum. Stratification was most commonly by sex or gender (n = 28, 42%), while vulnerable living conditions and disabilities were the least analysed (n = 1, 1%). No studies conducted stratified modelling analyses for religion or Plus factors. In 18 studies (6%), effect modification was assessed through interaction terms, with half involving sex or gender. The remaining studies explored the effects of race or ethnicity (n = 6, 33%), age (n = 6, 33%), education level (n = 3, 17%), income level (n = 2, 11%), rurality (n = 1, 6%) and immigration status (n = 1, 6%).

Further, 131 studies (72%) controlled for at least one PROGRESS-Plus factor as a confounding variable in their statistical analyses, and 61 (33%) studies collected and controlled for contextual factors in their research.

Completeness of equity reporting according to the proposed STROBE-Equity checklist

Over half of the studies (n = 197, 62%) described populations using PROGRESS-Plus factors in abstracts, and 75 (23%) assessed the results’ applicability across PROGRESS-Plus (Figure 2). 269 studies (84%) related their rationale to health equity, but only 18 (6%) defined health equity. Further, 36 studies (11%) described the relevance of health equity in exposure theory. The frequency of reporting at least one PROGRESS-Plus factor was 307 (96%) for participant demographics, 36 (11%) for missing data, 13 (4%) for participant loss or exclusion and 18 (6%) for flow diagrams. Overall, half of the studies (n = 166, 52%) contextualised their findings. A quarter (n = 77, 24%) considered applicability across PROGRESS-Plus factors, and 12 studies (4%) reported the implications of excluding people across one or more PROGRESS-Plus factors. 32 studies (10%) discussed contextual factors affecting equity when discussing generalisability (e.g. recruitment of Korean American immigrants from the Korean church as a cultural and social centre may also diminish the influence of socio-economic status and obesity-related health behaviours [41]).


Our study showed that despite many authors recognising equity’s importance, as indicated by over 80% providing a rationale for a focus on health equity, analysis and reporting by PROGRESS-Plus ranged from 0–95%, and almost half of the study design features relevant to equity were reported by less than 25% of articles. This work establishes a baseline assessment for reporting design features relevant to health equity in equity-relevant studies. The observed gaps and shortcomings directly underscore the need for more concerted efforts to address and improve the integration of health equity considerations in research practices. Importantly, these findings directly inform and shape the development of the STROBE-Equity reporting guideline, contributing to the establishment of a robust set of standards for comprehensive reporting of health equity dimensions in future observational studies.

Further, 5% of the studies explicitly mentioned using STROBE guidelines in this sample. A survey of a different sample of observational study authors found that 62% reported using STROBE guidelines [42]. This could suggest that there was over-reporting in that study or that there is less use of STROBE in this equity-focused sample than in that sample. When planning the implementation of STROBE-Equity to improve equity reporting, it will be important to consider how to raise awareness and use of both STROBE and STROBE-Equity amongst relevant audiences of researchers, funders, and journal editors.

This equity reporting assessment might overstate equity considerations in observational research as it focuses on equity-relevant studies which inherently address inequities. A broader analysis of studies could reveal less equity reporting. For instance, in 253 cardiac resynchronisation device studies [26], only 16% considered sex in the study design, and 26% reported sex-related effect sizes. Similarly, in 103 psychiatric studies using routinely collected health data [43], only 14% defined the target population by social determinants and assessed effect modification.

We found relatively few studies conducted in Africa and South America, with most low and middle-income papers from Asia, aligning with findings from a previous assessment of observational studies [44]. This may be a reflection that there are fewer studies published with lead authors from Africa and South America; thus, they had a smaller representation in our sample.

Our study followed a peer-reviewed protocol, ensuring balance across income settings, COVID-19 topics, and equity focus [32]. However, it has limitations. We assessed reported information, not ideal study conduct. Equity relevance judgments relied on abstracts, potentially missing eligible studies with different characteristics. Our search covered 2020–22, so global events like the COVID-19 pandemic and movements like Black Lives Matter may have increased mediated the consideration of equity in studies. Nevertheless, areas for improvement remain.

The relatively high proportion of subgroup analyses across PROGRESS-Plus factors (65%) is explained by the cross-sectional studies included in our sample. Authors frequently disaggregate outcome data by participant characteristics and cross-tabulate them in Table 1 of cross-sectional study manuscripts (114/220 cross-sectional studies). We found that 21% of studies that assessed PROGRESS-Plus factors as effect modifiers, which is slightly higher than in two previous evaluations of substantive areas (14% in 103 studies of mental health and 13% in 253 studies of heart failure) [26,43] Nonetheless, the reporting of one or more PROGRESS-Plus factor in these studies suggests that there were missed opportunities to explore the role of these factors in effect modification.

Equity considerations in study design and methodology were rarely integrated and reported. Only eight studies reported engaging interest holders experiencing inequities, and just 22 considered equity-related characteristics when determining sample size. Engaging interest holders (alternative term to stakeholders that is more suitable [45]) is a priority supported by leading organisations [4649] and guidance regarding the matter is improving [5054]. We recognise the challenges with attaining and sustaining the engagement of members of populations yet advise engaging interest holders, particularly representatives of populations experiencing inequities. It is also a possibility that the engagement of interest holders might have been underreported [55].

The observational studies we included seldom reported efforts to reduce selection bias, like adapting recruitment methods to reach marginalised populations [56,57]. Such adaptations are likely ineffective without engaging these populations in the research. This is especially crucial in studies using routinely collected data. Populations facing social exclusion, such as those experiencing homelessness, substance dependence, sex work, migration, or incarceration, are often excluded or unidentifiable in administrative health data [58,59]. Furthermore, their indicators of social exclusion are not systematically recorded or are inconsistent [59,60]. Failing to consider these factors in observational studies means missing opportunities to generate evidence for these populations.

Mitigating health inequities requires analysing underlying processes like racism and discrimination [6163]. Observational studies can support this by describing their analytical approach, using logic models, and incorporating health equity in interventions and outcomes. Assessing evidence applicability to populations experiencing inequities is essential for achieving health policy goals, such as the Sustainable Development Goals [14]. Standardising this assessment in all research is crucial, as suggested by our patient advisors.

The findings of this study serve as a baseline assessment for reporting health equity in studies pertaining to equity. The observed gaps and shortcomings directly underscore the need for more concerted efforts to address and improve the integration of health equity considerations in research practices. Importantly, these findings directly inform and shape the development of the STROBE-Equity reporting guideline, contributing to the establishment of a robust set of standards for comprehensive reporting of health equity dimensions in future observational studies. Adherence to these guidelines will enhance the knowledge base regarding the impact of health care practices and policies on health equity and help readers understand what was done and what was found in the research. This will ultimately enhance fairness in the promotion and protection of health.


Improving equity data are vital for achieving global goals to ‘leave no-one behind’ [64]. Our study revealed a prevalent recognition of equity’s importance among observational studies published during 2020–23 during which the COVID pandemic was active; however, reporting health equity considerations demonstrates high variability and notable inadequacies. These findings will inform the consensus meeting for our planned STROBE statement equity extension. We are planning an integrated and end-of-grant knowledge translation strategy to disseminate and encourage uptake of STROBE-Equity that is aimed at reaching researchers, funders, research ethics boards and journal editors, all of whom have a role to play in enhancing transparent reporting of health equity in observational studies. Adherence to these guidelines will enhance the knowledge base regarding the impact of health care practices and policies on health equity. This will ultimately enhance fairness in the promotion and protection of health. We invite the scientific community and the public to stay updated on the STROBE-Equity project on our Open Science Framework project page [65].

Additional material

Online Supplementary Document


We are grateful to Marshall Dozier, the Academic Support Librarian at the University of Edinburgh, UK, for her assistance in developing the search strategies.

Ethics statement: No ethics approval was required for the purpose of this study.

Data availability: Data is available upon request from the corresponding author.

[1] Funding: This work was supported by the Canadian Institutes of Health Research (CIHR), grant number 173269.

[2] Authorship contributions: LM, VW, SF and JJ are all co-principal investigators of the project and were responsible for funding acquisition and conceptualisation. OD, VW and LM are responsible for the design of the methodology. All authors are part of the STROBE-Equity Steering Committee and approved the methods used in the manuscript. VW and LM were responsible for project administration and supervision. They have both contributed equally to this project. TR was responsible for designing the search strategies. OD, AA, MB, LA, JH, AJ, LB, NE, EG conducted the investigation and collected the data. OD and LM carried out the formal analysis. OD visualised the findings and wrote the original draft of the manuscript. The remaining authors critically reviewed the manuscript, provided feedback and approved the final manuscript.

[3] Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and declare the following activities and relationships: LGC is employed by the Pan American Health Organization (PAHO/WHO). The ideas expressed in this manuscript are the authors’ own and do not necessarily reflect the decisions and policies of PAHO/WHO. The remaining authors have no conflicts to declare.


[1] Wilson S, Breen A, Dupré L. Research and Reconciliation Unsettling Ways of Knowing through Indigenous Relationships. Toronto: Canadian Scholars; 2019.

[2] World Health Organization. Health inequities and their causes. 2018. Available: Accessed: 25 May 2022.

[3] GC Gee and CL Ford. STRUCTURAL RACISM AND HEALTH INEQUITIES: Old Issues, New Directions. Du Bois Rev. 2011;8:115-32. DOI: 10.1017/S1742058X11000130. [PMID:25632292]

[4] M Whitehead. The concepts and principles of equity and health. Int J Health Serv. 1992;22:429-45. DOI: 10.2190/986L-LHQ6-2VTE-YRRN. [PMID:1644507]

[5] Government of Canada. Gender-based analysis plus (GBA+). 2022. Available: Accessed: 25 May 2022.

[6] A Peterson, V Charles, D Yeung, and K Coyle. The Health Equity Framework: A Science- and Justice-Based Model for Public Health Researchers and Practitioners. Health Promot Pract. 2021;22:741-6. DOI: 10.1177/1524839920950730. [PMID:32814445]

[7] DC Dover and AP Belon. The health equity measurement framework: a comprehensive model to measure social inequities in health. Int J Equity Health. 2019;18:36 DOI: 10.1186/s12939-019-0935-0. [PMID:30782161]

[8] J O’Neill, H Tabish, V Welch, M Petticrew, K Pottie, and M Clarke. Applying an equity lens to interventions: using PROGRESS ensures consideration of socially stratifying factors to illuminate inequities in health. J Clin Epidemiol. 2014;67:56-64. DOI: 10.1016/j.jclinepi.2013.08.005. [PMID:24189091]

[9] V Welch, O Dewidar, E Tanjong Ghogomu, S Abdisalam, A Al Ameer, and VI Barbeau. How effects on health equity are assessed in systematic reviews of interventions. Cochrane Database Syst Rev. 2022;1:MR000028. [PMID:35040487]

[10] RC Brownson, SK Kumanyika, MW Kreuter, and D Haire-Joshu. Implementation science should give higher priority to health equity. Implement Sci. 2021;16:28 DOI: 10.1186/s13012-021-01097-0. [PMID:33740999]

[11] VA Welch, OF Norheim, J Jull, R Cookson, H Sommerfelt, and P Tugwell. CONSORT-Equity 2017 extension and elaboration for better reporting of health equity in randomised trials. BMJ. 2017;359:j5085 DOI: 10.1136/bmj.j5085. [PMID:29170161]

[12] V Welch, M Petticrew, P Tugwell, D Moher, J O’Neill, and E Waters. PRISMA-Equity 2012 extension: reporting guidelines for systematic reviews with a focus on health equity. PLoS Med. 2012;9:e1001333. DOI: 10.1371/journal.pmed.1001333. [PMID:23222917]

[13] VA Welch, EA Akl, G Guyatt, K Pottie, J Eslava-Schmalbach, and MT Ansari. GRADE equity guidelines 1: considering health equity in GRADE guideline development: introduction and rationale. J Clin Epidemiol. 2017;90:59-67. DOI: 10.1016/j.jclinepi.2017.01.014. [PMID:28412464]

[14] M Marmot and R Bell. The Sustainable Development Goals and Health Equity. Epidemiology. 2018;29:5-7. DOI: 10.1097/EDE.0000000000000773. [PMID:29053554]

[15] A Antequera, DO Lawson, SG Noorduyn, O Dewidar, M Avey, and ZA Bhutta. Improving Social Justice in COVID-19 Health Research: Interim Guidelines for Reporting Health Equity in Observational Studies. Int J Environ Res Public Health. 2021;18:9357 DOI: 10.3390/ijerph18179357. [PMID:34501949]

[16] Reeves BC, Deeks JJ, Higgins JP, Shea B, Tugwell P, Wells GA. Chapter 24: Including non-randomized studies on intervention effects. In: Higgins JPT, Thomas J, editors. Cochrane Handbook for Systematic Reviews of Interventions, v 6.2 (updated February 2021). UK: Cochrane; 2021. Available: Accessed: 26 February 2024.

[17] E von Elm, DG Altman, M Egger, SJ Pocock, PC Gøtzsche, and JP Vandenbroucke. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007;335:806-8. DOI: 10.1136/bmj.39335.541782.AD. [PMID:17947786]

[18] RE Glover, MCI van Schalkwyk, EA Akl, E Kristjannson, T Lotfi, and J Petkovic. A framework for identifying and mitigating the equity harms of COVID-19 policy interventions. J Clin Epidemiol. 2020;128:35-48. DOI: 10.1016/j.jclinepi.2020.06.004. [PMID:32526461]

[19] MW Tenforde, KA Fisher, and MM Patel. Identifying COVID-19 Risk Through Observational Studies to Inform Control Measures. JAMA. 2021;325:1464-5. DOI: 10.1001/jama.2021.1995. [PMID:33616617]

[20] Pan American Health Organization. Guidance for implementing non pharmacological public health measures in populations in situations of vulnerability in the context of COVID-19. Washington, DC: Pan American Health Organization; 2020. Available: Accessed: 25 May 2022.

[21] Y Jin, N Sanger, I Shams, C Luo, H Shahid, and G Li. Does the medical literature remain inadequately described despite having reporting guidelines for 21 years? – A systematic review of reviews: an update. J Multidiscip Healthc. 2018;11:495-510. DOI: 10.2147/JMDH.S155103. [PMID:30310289]

[22] A Stevens, L Shamseer, E Weinstein, F Yazdi, L Turner, and J Thielman. Relation of completeness of reporting of health research to journals’ endorsement of reporting guidelines: systematic review. BMJ. 2014;348:g3804 DOI: 10.1136/bmj.g3804. [PMID:24965222]

[23] L Turner, L Shamseer, DG Altman, KF Schulz, and D Moher. Does use of the CONSORT Statement impact the completeness of reporting of randomised controlled trials published in medical journals? A Cochrane review. Syst Rev. 2012;1:60 DOI: 10.1186/2046-4053-1-60. [PMID:23194585]

[24] NH Münter, A Stevanovic, R Rossaint, C Stoppe, RD Sanders, and M Coburn. CONSORT item adherence in top ranked anaesthesiology journals in 2011: A retrospective analysis. Eur J Anaesthesiol. 2015;32:117-25. DOI: 10.1097/EJA.0000000000000176. [PMID:25387297]

[25] MK Sharp, L Bertizzolo, R Rius, E Wager, G Gómez, and D Hren. Using the STROBE statement: survey findings emphasized the role of journals in enforcing reporting guidelines. J Clin Epidemiol. 2019;116:26-35. DOI: 10.1016/j.jclinepi.2019.07.019. [PMID:31398440]

[26] O Dewidar, I Podinic, V Barbeau, D Patel, A Antequera, and D Birnie. Integrating sex and gender in studies of cardiac resynchronization therapy: a systematic review. ESC Heart Fail. 2022;9:420-7. DOI: 10.1002/ehf2.13733. [PMID:34821083]

[27] Park H, Dewidar O, Tanjong-Ghogomu E, Welch V. Reporting and analysis of Sex and Gender in Transitions of Care for Older Adults: A Methods Study. University of Ottawa Journal of Medicine. 2022;11.

[28] I Jahn, C Börnhorst, F Günther, and T Brand. Examples of sex/gender sensitivity in epidemiological research: results of an evaluation of original articles published in JECH 2006–2014. Health Res Policy Syst. 2017;15:11 DOI: 10.1186/s12961-017-0174-z. [PMID:28202078]

[29] S Funnell, J Jull, L Mbuagbaw, V Welch, O Dewidar, and X Wang. Improving social justice in observational studies: protocol for the development of a global and Indigenous STROBE-equity reporting guideline. Int J Equity Health. 2023;22:55 DOI: 10.1186/s12939-023-01854-1. [PMID:36991403]

[30] MJ Page, JE McKenzie, PM Bossuyt, I Boutron, TC Hoffmann, and CD Mulrow. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71 DOI: 10.1136/bmj.n71. [PMID:33782057]

[31] S Staniszewska, J Brett, I Simera, K Seers, C Mockford, and S Goodlad. GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research. BMJ. 2017;358:j3453 DOI: 10.1136/bmj.j3453. [PMID:28768629]

[32] O Dewidar, T Rader, H Waddington, SG Nicholls, J Little, and BJ Hardy. Reporting of health equity considerations in equity-relevant observational studies: Protocol for a systematic assessment[version 1; peer review: awaiting peer review] F1000 Res. 2022;11:615 DOI: 10.12688/f1000research.122185.1

[33] J McGowan, M Sampson, DM Salzwedel, E Cogo, V Foerster, and C Lefebvre. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol. 2016;75:40-6. DOI: 10.1016/j.jclinepi.2016.01.021. [PMID:27005575]

[34] SL Prady, EP Uphoff, M Power, and S Golder. Development and validation of a search filter to identify equity-focused studies: reducing the number needed to screen. BMC Med Res Methodol. 2018;18:106 DOI: 10.1186/s12874-018-0567-x. [PMID:30314471]

[35] British Medical Journal. Study design search filters: BMJ Best Practice. Available: Accessed: 25 May 2022.

[36] McMaster University. Search Filters for MEDLINE in Ovid Syntax and the PubMed translation. 2022. Available: Accessed: 25 May 2022.

[37] J Jull, M Whitehead, M Petticrew, E Kristjansson, D Gough, and J Petkovic. When is a randomised controlled trial health equity relevant? Development and validation of a conceptual framework. BMJ Open. 2017;7:e015815. DOI: 10.1136/bmjopen-2016-015815. [PMID:28951402]

[38] SR DistillerHomepage. 2022. Available: Accessed: 25 May 2022.

[39] UKCRC Health Research Classification System. Health Categories. 2022. Available: Accessed: 25 May 2022.

[40] World Health Organization. Determinants of health. 2017. Available: Accessed: 25 May 2022.

[41] M Jang, S Jeon, S Nam, H-J Song, and R Whittemore. Relationships of Obesity-Related Behavior Patterns With Socioeconomic Status and Acculturation in Korean American Women. Clin Nurs Res. 2020;29:440-7. DOI: 10.1177/1054773818783467. [PMID:29932007]

[42] MK Sharp, R Tokalić, G Gómez, E Wager, DG Altman, and D Hren. A cross-sectional bibliometric study showed suboptimal journal endorsement rates of STROBE and its extensions. J Clin Epidemiol. 2019;107:42-50. DOI: 10.1016/j.jclinepi.2018.11.006. [PMID:30423373]

[43] LC Barker, N Hussain-Shamsy, KL Rajendra, SE Bronskill, HK Brown, and P Kurdyak. The use of key social determinants of health variables in psychiatric research using routinely collected health data: a systematic analysis. Soc Psychiatry Psychiatr Epidemiol. 2023;58:183-91. DOI: 10.1007/s00127-022-02368-x. [PMID:36149450]

[44] R Zachariah, S Rust, P Thekkur, M Khogali, AM Kumar, and K Davtyan. Quality, Equity and Utility of Observational Studies during 10 Years of Implementing the Structured Operational Research and Training Initiative in 72 Countries. Trop Med Infect Dis. 2020;5:167 DOI: 10.3390/tropicalmed5040167. [PMID:33172059]

[45] J Petkovic, O Magwood, L Lytvyn, J Khabsa, TW Concannon, and V Welch. Key issues for stakeholder engagement in the development of health and healthcare guidelines. Res Involv Engagem. 2023;9:27 DOI: 10.1186/s40900-023-00433-6. [PMID:37118762]

[46] British Medical Journal. Patient and public partnership. 2014. Available: Accessed: 25 May 2022.

[47] US Deprescribing Research Network. Engaging Stakeholders in Research. 2022. Available: Accessed: 25 May 2022.

[48] WM den Oudendammer, J Noordhoek, RY Abma-Schouten, L van Houtum, JEW Broerse, and CWM Dedding. Patient participation in research funding: an overview of when, why and how amongst Dutch health funds. Res Involv Engagem. 2019;5:33 DOI: 10.1186/s40900-019-0163-1. [PMID:31720008]

[49] L Holmes, K Cresswell, S Williams, S Parsons, A Keane, and C Wilson. Innovating public engagement and patient involvement through strategic collaboration and practice. Res Involv Engagem. 2019;5:30 DOI: 10.1186/s40900-019-0160-4. [PMID:31646001]

[50] Canadian Institutes of Health Research. Strategy for Patient-Oriented Research – Patient Engagement Framework. 2019. Available: Accessed: 25 May 2022.

[51] A Boaz, S Hanney, R Borst, A O’Shea, and M Kok. How to engage stakeholders in research: design principles to support improvement. Health Res Policy Syst. 2018;16:60 DOI: 10.1186/s12961-018-0337-6. [PMID:29996848]

[52] J Martinez, C Wong, CV Piersol, DC Bieber, BL Perry, and NE Leland. Stakeholder engagement in research: a scoping review of current evaluation methods. J Comp Eff Res. 2019;8:1327-41. DOI: 10.2217/cer-2019-0047. [PMID:31736341]

[53] J Martínez, CV Piersol, K Lucas, and NE Leland. Operationalizing Stakeholder Engagement Through the Stakeholder-Centric Engagement Charter (SCEC). J Gen Intern Med. 2022;37:Suppl 1105-8. DOI: 10.1007/s11606-021-07029-4. [PMID:35349021]

[54] JR Kirwan, M de Wit, L Frank, KL Haywood, S Salek, and S Brace-McDonnell. Emerging Guidelines for Patient Engagement in Research. Value Health. 2017;20:481-6. DOI: 10.1016/j.jval.2016.10.003. [PMID:28292494]

[55] S Vanderhout, P Nevins, SG Nicholls, C Macarthur, JC Brehaut, and BK Potter. Patient and public involvement in pragmatic trials: online survey of corresponding authors of published trials. CMAJ Open. 2023;11:E826-E837. DOI: 10.9778/cmajo.20220198. [PMID:37726115]

[56] J Russomanno, JG Patterson, and JM Jabson Tree. Social Media Recruitment of Marginalized, Hard-to-Reach Populations: Development of Recruitment and Monitoring Guidelines. JMIR Public Health Surveill. 2019;5:e14886. DOI: 10.2196/14886. [PMID:31789598]

[57] K Doran, A Collado, H Taylor, JW Felton, KN Tormohlen, and R Yi. Methods to Optimize Recruitment, Participation, and Retention Among Vulnerable Individuals Participating in a Longitudinal Clinical Trial. Res Theory Nurs Pract. 2021;35:24-49. DOI: 10.1891/RTNP-D-19-00039. [PMID:33632921]

[58] United Nations. Leaving no one behind: The imperative of inclusive development. 2016. Available: Accessed: 25 May 2022.

[59] RW Aldridge, A Story, SW Hwang, M Nordentoft, SA Luchenski, and G Hartwell. Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. Lancet. 2018;391:241-50. DOI: 10.1016/S0140-6736(17)31869-X. [PMID:29137869]

[60] E Tweed, A Leyland, D Morrison, and SV Katikireddi. Using cross-sectoral data linkage to understand the health of people experiencing multiple exclusion. European Journal of Public Health.2020; 30(Supplement_5). ckaa165.052.

[61] DR Williams and LA Cooper. Reducing Racial Inequities in Health: Using What We Already Know to Take Action. Int J Environ Res Public Health. 2019;16:606 DOI: 10.3390/ijerph16040606. [PMID:30791452]

[62] National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Population Health and Public Health Practice; Committee on Community-Based Solutions to Promote Health Equity in the United States. Communities in Action: Pathways to Health Equity. Baciu A, Negussie Y, Geller A, Weinstein JN, editors. Washington (DC): National Academies Press (US); 2017. Available: Accessed: 25 May 2022.

[63] E Curtis, R Jones, D Tipene-Leach, C Walker, B Loring, and SJ Paine. Why cultural safety rather than cultural competency is required to achieve health equity: a literature review and recommended definition. Int J Equity Health. 2019;18:174 DOI: 10.1186/s12939-019-1082-3. [PMID:31727076]

[64] World Health Organization. World health statistics 2019: monitoring health for the SDGs, sustainable development goals. Geneva: World Health Organization; 2019. Available: Accessed: 25 May 2022.

[65] V WelchA RizviO DewidarSTROBE-equity reporting guidelines. 2020. Available: Accessed: 25 May 2022.

Correspondence to:
Vivian Welch
Bruyère Research Institute
85 Primrose Ave, Ottawa
[email protected]