Overweight and obesity are associated with increased risk of developing common diseases that can cause premature death. These include type 2 diabetes, cardiovascular disease, liver disease, and some cancers and respiratory diseases [1]. There is also a bidirectional association between obesity and depression [2]. Overweight and obesity is therefore a complex condition conferring significant health, social care, and financial burden, which requires carefully designed countermeasures and interventions throughout the life cycle [3]. A person is currently considered overweight if their BMI (the ratio of mass in kg to squared height in meters) is ≥25kg/m², and obese if their BMI is ≥30 kg/m² [4]. Overweight and obesity is a growing health problem. Global obesity rates have more than doubled since 1980, with the mean (95% CI) BMI in the United Kingdom rising from 24.7 (24.4-25.0) kg/m² in 1986 to 27.1 (26.8-27.5) kg/m² in 2016 [5]. Tackling overweight and obesity is therefore an urgent public health emergency for policy makers, clinicians, and researchers, as well as the individual themselves [6,7].

Independent studies globally have confirmed that low socioeconomic status (SES) is associated with increased rates of overweight and obesity (eg, in China [8], the United States and France [9], and the United Kingdom [10]). Several parameters need to be assessed to measure SES including an individual’s income, educational level, and occupation [11]. Other measures exist such as the Indices of Deprivation, used in England, which also includes exposure to crime, health, housing, and living environment domains [12]. These measures have been used to provide compelling evidence that deprivation is associated with worse health behaviors and outcomes; those who live in more deprived areas are more likely to engage in unhealthy behaviors (smoking, increased alcohol consumption) and less likely to engage in healthy behaviors (physical activity, healthy diet) compared with those in less deprived areas [13]. Thus, SES should be considered a confounding factor in studies determining the efficacy of weight management interventions if the intervention adopts behavior change approaches [6].

It is not surprising therefore that traditional behavior change interventions that target unhealthy behaviors in low SES groups have reported modest improvements in weight and physical fitness compared to people from higher SES. For example, meta-analyses estimated modest standardized mean differences (95% CI) between low-income groups and controls of 0.22 (0.14-0.29) following diet interventions, 0.21 (0.06-0.36) following physical activity interventions, and a relative risk of smoking following abstinence interventions of 1.59 (1.34-1.89) [14]. In a qualitative study of people delivering, receiving, and following an eating lifestyle change intervention in a low SES community, incorporation of diverse language/literacy, cultural origin, and the availability/cost of healthy foods and physical activity options were important factors that could lead to more equitable success in weight loss [15]. This study acknowledged that not adapting interventions that are less efficacious for people with low SES would increase existing inequalities across SES groups. However, it also acknowledged that a dearth of literature is available with which to plan what to adapt (and how), and its results certainly help to address this by tailoring the service to multiple cultures and lobbying for fair local amenity access. What this welcome study did not include as a factor was any personal choice in the medium of weight loss interventions.

eHealth is defined as interventions delivered using computers, mobile phones, or similar media devices via internet websites/web applications; mobile or social network apps; email; or SMS text messaging [16]. It is possible that technological advances mean eHealth interventions can be offered as an alternative approach for low SES patients. Traditional weight management interventions typically require frequent face-to-face sessions. However, individuals from low SES have expressed barriers to physically attending health care appointments, which include stress arising from taking time off work, and excessive travel and childcare costs within limited personal budgets. It is therefore possible that eHealth options may be preferred by low SES individuals [17,18]. Prioritizing the use of technology may also help reach diverse groups that are often underrepresented in research and real-world interventions [19].

Ambitions for eHealth have been transparent in the UK National Health Service (NHS) over the last decade. NHS England’s Five Year Forward View alluded to the health care opportunities afforded by the “information revolution” and “electronic glue” [20]. More recently, one of the NHS Long Term Plan aims was to increase the percentage of “digital access” options for services available for patients’ care, with 100% of patients being offered a “digital-first” primary care consultation by 2023/24 [21]. There is also the acceleration of eHealth uptake in response to the COVID-19 pandemic, culminating in recent guidance from NHS England that 25% of all outpatient health consultations in secondary care should be offered remotely via telephone or video [22]. Given these ambitions and the eHealth evolution, there is no doubt the direction of travel for weight management interventions incorporates eHealth options. Although a large meta-analysis demonstrated that eHealth weight management interventions achieve statistically significant weight loss compared to controls [19], the analyses did not account for SES. Thus, it remains unclear whether eHealth options could lead to more equity in weight management intervention outcomes independent of SES.

We propose to undertake a systematic review of the literature and determine what eHealth weight management interventions are offered and whether they are effective in facilitating weight loss and physical fitness and activity gains in people with low SES. The primary aim of this study is to first determine what eHealth weight management interventions exist in promoting weight loss and improving physical activity and fitness for people living with overweight and obesity from low SES groups, and second evaluate their efficacy. The proposed systematic review aims to answer the following questions:

This systematic review will be conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement [23]. The protocol has been reported according to the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols) checklist [24] (Multimedia Appendix 1).

Eligibility criteria were structured using a PICOS (Population, Intervention, Comparison, Outcomes, and Study design) framework [25] (Table 1).

Adults aged ≥18 years who are living with overweight or obese (BMI ≥25 kg/m²) at baseline and are from a low SES background will be included. Low SES will include either low educational level, low income, or low occupational status, or any combination of these [11] (Table 2). The term “low” will refer to less well paid occupational status, fewer years of academic study, and lower income or a similar social disadvantage [26]. Individual studies will need to have defined SES based on stated criteria to be included. Studies including adults and children may be considered if data reported for adults are recorded separately. All participants with comorbidities will be included due to known associations of overweight and obesity with other health conditions [27].

Studies will be included if their weight management intervention aims include weight loss, weight loss maintenance, and physical fitness, and/or physical activity increase. Intervention mechanisms will be included if they include those recommended by the National Institute for Health and Care Excellence (NICE) guidelines [30] for weight management programs and include behavior change, diet, and nutrition education, meal replacement interventions, physical activity advice, and activity and exercise. Studies that involve one or more domain as outlined by NICE [30] will be considered for inclusion as previous literature has identified large variations in published eHealth interventions [16,19]. Interventions will be eligible if they include a single or range of eHealth technology to deliver content, which may be delivered via the web, mobile apps, mobile phones, computers, or other related devices that require participants to be engaged. We will exclude studies involving bariatric surgery or obesity medication only interventions.

No limitation will be imposed on the control group. Studies with or without a control group will be considered eligible.

The primary outcomes of interest are weight (kg) and BMI (kg/m²) either in absolute or proportional terms. Secondary outcomes will include any anthropometric or fitness measures including (but not limited to) body composition, percentage change of lean muscle mass, VO_2max (maximum oxygen consumption), estimated VO_2max, predicted VO_2peak (volume of oxygen uptake during peak exercise), aerobic capacity, and physical activity levels. We have included a large range of outcomes to counter the expected large variation among studies. A combination of anthropometric measures and cardiorespiratory fitness measures have been considered to ensure a breadth of results are included. All outcomes will be included for data extraction if secondary measurement has been made in addition to baseline to evaluate the effect of the intervention.

We will include experimental and observational cohort studies designed to describe and/or investigate the efficacy of eHealth interventions. Experimental trials will include randomized control trials (RCTs), controlled clinical trials, or cluster trials. Observational studies will include prospective and retrospective comparative cohort studies, and cross-sectional, case-control, or nested case-control studies. We will exclude review articles, secondary analysis, and case study articles.

There will be no restrictions on the length of follow-up of outcomes.

There will be no restrictions by type of setting as interventions will be by remote access.

Only studies written in the English language will be included.

Literature search strategies will be developed using medical subject headings (MeSH) and text words related to the eligibility criteria outlined (Multimedia Appendix 2). We will search MEDLINE, Embase, Emcare, and CINAHL electronic databases. Both subject header and free-text searches will be completed, using Boolean search techniques, based on our PICOS framework (Table 1). Weight management and eHealth search terms were based on a previously published systematic review [16]. The grey literature will be searched using OpenGrey [31], and completed master’s and doctoral theses will be searched using E-Theses Online Service (EThOS) [32]. All databases will be searched from their respective inception dates.

We will conduct a narrative synthesis on all available data, examining findings between and within studies following national guidelines [25]. The narrative synthesis will include an account of interventions (eg, eHealth), participants’ characteristics, and outcomes.

If an adequate number of homogeneous studies in terms of participants, intervention, and outcomes are returned, the individual outcomes will be pooled quantitatively using a fixed- and random-effects meta-analysis.

In the event that the protocol needs amending, we will provide dates of each amendment, describe the changes, and give rationale in the section.