Executive summary

Obesity and the economy

Obesity cost the UK £107 billion in 2025; including approximately £24 billion in productivity costs and £9 billion in NHS costs according to a report published by Frontier Economics, commissioned by Nesta. Despite the clear economic benefits of reducing obesity, there is currently limited evidence on the potential economic impact of weight loss medications in the UK. NHS England has planned a 12-year rollout of the weight loss drug tirzepatide, including via primary care, to 1.6 million adults[^1], which would target ~9% of adults currently living with obesity. There is a need for greater evidence related to the economic benefits to understand how a more rapid rollout could support economic growth.

The key findings of this report provides some notable evidence in this area:

The Nesta-Oviva Collaboration

Nesta is an innovation and research foundation with a goal to halve obesity prevalence in the UK by 2030. Oviva is an approved NHS provider offering a Tier-3 digital weight management programme (including prescription of weight loss drug, semaglutide) to 37,000 NHS UK Tier-3 patients over 10 years.

Oviva and Nesta have partnered to better understand the wider potential benefits of weight loss medications beyond direct health outcomes. By analysing Oviva's real-world self-reported data from ~2,000 NHS patients with obesity, we have examined the impact of the programme on sickness absence, employment status and use of healthcare services.

Key Finding 1: Clinical weight loss

The clinical effects of this programme align with results from randomised trials of semaglutide, observing an average of 17% reduction in body weight over a 12 month period.

Key Finding 2: Potential economic gains due to reduced sickness absence

Oviva patients were asked to report sickness absence for the 3 months preceding a baseline survey and the 3 months preceding a 12 month follow-up survey. For employed patients, absences due to sickness fell by around 30%, from an average of 1.3 days at baseline to 0.9 days 12 months later.

We converted the odds of reducing sickness absence into a total potential saving using cost assumptions and methodology from previous publications (Analysis by Frontier Economics). When scaling the findings to the planned NHS rollout - 1.6 million people receiving tirzepatide over 12 years - the potential economic gain is estimated as £150m - £300m

Key Finding 3: Potential health service costs saved

At 12 month follow-up, Oviva participants reported using less GP and hospital appointments in both face to face and remote formats. This finding is statistically significant.

Across the 1,992 participants, total hospital visits reduced by 31% from 2,707 appointments at baseline survey to 1,869 visits at 12-month survey. In addition, total GP visits reduced by 47% from 5,627 visits to 3,000 visits. In total, we estimate total potential savings of at least £200,000 over the 3-month period preceding 12 months. It was not reported whether the appointments were self funded (private) or NHS appointments.

The sample analysed accounts for 0.1% of the planned 1.6m NHS rollout. If the same reduction was observed at scale and sustained beyond the 3 month period, it could result in meaningful health care savings. It is not clear how this would scale to 1.6 million people, given the difference a wider sample would have with regards to baseline BMI and healthcare use. However, to take a conservative estimate and assume reductions in appointments at half the rate observed in these analyses would result in about £80 million in cost savings for 1.6 million people.

Policy implications

This real world evidence suggests that there could be important economic benefits associated with weight loss medications, potentially improving their cost-effectiveness and strengthening the case for a faster and wider NHS rollout. It would also reduce health inequality by ensuring these treatments reach lower-income populations - who are statistically more affected by obesity - but are currently priced out of a private market that favours those with the means to pay.

The findings, based on self-reported associations between weight loss medications and economic and health system outcomes, suggest that there are meaningful economic benefits to weight loss medications. However, these gains are only sustainable if the observed improvements are maintained, as evidence highlights the risk of weight regain at cessation of treatment. Hence these findings should be interpreted as representative of active treatment effects. Furthermore, as this study examined only a subset of the total obesity costs identified in previous reports, future evidence will likely provide a more comprehensive picture of the medications' full economic impact.

For national policy, the primary implication is that the cost of these medications can be partially offset by economic gains. Currently only ~9% of people living with obesity will have access to these medications under the NHS over 12 years, so there is a huge gap in access for those with the highest clinical need. These results strengthen the case to deliver on existing commitments, increase the scale and pace of the rollout to ensure equitable access and regularly re-evaluate the cost-effectiveness as more evidence emerges.

The approach to support those most in need with weight loss medications must be supplemented with a critical need to ensure healthier food is more available, accessible and affordable. Policies such as the Healthy Food Standard remain the most cost-effective and long-lasting drivers of obesity prevention and reduction. By combining expanded medical access with robust preventative policy, the UK can create a sustainable, long-term solution to the obesity crisis.

A note on causality: All analyses are based on self-reported patient data and, due to the nature of the study design and available data, there is no control group. As a result, causality cannot be inferred from these analyses. The findings reported reflect changes associated with the passage of time, and it is possible that factors other than participation in Oviva's programme contributed to the observed changes. This approach is a pragmatic analytical approach and we are currently working on methodologies to improve the robustness of estimating economic benefits. If you - or your organisation - are interested in this work, please contact the authors of the report.

Introduction

Our partnership

Nesta, an innovation and research foundation, aims to halve obesity prevalence in the UK by 2030. Nesta's research shows the crisis is solvable, requiring only an 8.5% daily calorie reduction for those with excess weight, which is achievable through many small changes in the food system. To reach the target, we know that alongside changes to the food system, we need to support those who need it with evidence-based treatments.

Oviva is a digital-first weight management provider that delivers GLP-1 medications alongside virtual coaching and app-based behavioural nudges, educational content, and monitoring. Through this integrated approach, Oviva supports patients in building sustainable habits and achieving clinically significant weight loss and holistic health improvements.

The economic impact of obesity

Obesity is a major public health and economic challenge in the UK. Since 1990, the prevalence of obesity has doubled, and around two-thirds of adults are now living with excess weight (overweight or obesity). This trend is placing growing pressure on individuals, employers, public services, and the wider economy.

According to analysis by Frontier Economics (commissioned by Nesta), excess weight currently costs the UK economy an estimated £126 billion each year. About £31 billion of this total is linked to reduced economic productivity. This includes £8.3 billion from sickness absence and £9.7 billion from reduced productivity among people in work. A further £12.7 billion is associated with economic inactivity resulting from unemployment, early retirement, and premature mortality linked to excess weight.

Excess weight is also associated with lower levels of labour market participation. Employment rates among people living with Class III obesity are 70%, compared with 76% among those at a healthy weight.[^3] For individuals living with Class I or II obesity, employment rates are 74%. These lower employment rates are estimated to cost the economy £8.5 billion annually, equivalent to approximately £800 per working-age adult aged 18-64.

Without effective action, these costs are projected to rise further. Driven by increasing obesity prevalence and population growth, the annual economic burden of excess weight is expected to reach £150 billion by 2035. This highlights the need for coordinated policy interventions that improve population health while reducing long-term pressures on employers, healthcare systems, and the wider economy.

If obesity prevalence was to halve (to 16%) and overweight prevalence was halved (to 33%), productivity costs would amount to approximately £12 billion.

As well as productivity losses, health service use contributes to the total economic cost of excess weight. The financial cost of treating illnesses associated with excess weight comes at a cost of approximately £13 billion.

The current GLP-1 landscape

GLP-1 receptor agonists such as semaglutide and tirzepatide represent a notable development in the treatment of obesity, providing clinical weight-loss outcomes that exceed those of previous pharmacological interventions.

In 2024, the National Institute for Health and Care Excellence (NICE) published draft guidance recommending tirzepatide for NHS patients with a BMI of 35 or above, or 32.5 or above for certain ethnic minority groups, including South Asian and Black African populations, who also have at least one obesity-related health condition. If implemented, this would make the UK the first publicly funded healthcare system to provide widespread access to GLP-1 treatments through primary care.

NHS England have subsequently requested a longer implementation timeline, citing concerns around affordability, service capacity, and equitable access. As a result, the rollout was significantly reduced in scale and pace. Rather than reaching an estimated 3.4 million people within five years, the revised plan aims to provide treatment to approximately 220,000 patients over the first three years, with full rollout to 1.6 million people now expected over a 12-year period. Stakeholders have raised concerns that this slower implementation will limit the NHS's ability to respond to rising obesity prevalence in the UK.

Taking into account private market access as well, survey data indicates that as of early 2025, approximately 1.6 million people in Great Britain had used GLP-1s for weight loss. The majority of access is through private online pharmacies. Data from the Institute of Grocery Distribution in April 2026 suggests that uptake of weight loss medications grew from 3% in June 2025 to 6% in March 2026.

The evidence gap

Existing data regarding weight loss interventions, such as bariatric surgery, offer inconsistent findings concerning workforce participation, making it difficult to extrapolate the potential economic impact of GLP-1 therapies. While the government has commissioned a multi-year, real-world evaluation of the NHS tirzepatide rollout, comprehensive findings are not projected to be available for several years, creating an immediate need for supplementary insight.

This analysis builds upon 2025 analysis conducted by Oviva, which demonstrated promising short-term benefits of a digitally delivered Tier-3 weight management programme after 6 months. That pilot served as a proof of concept, revealing an improvement in both health and economic outcomes: the proportion of participants reporting zero sick leave increased from 63% to 78%, while GP consultations decreased by 40% over a six-month period.

To address the current evidence gap, this analysis is designed to examine changes in patient productivity outcomes (employment status and self-reported sick days) after 12 months in Oviva's digital Tier-3 weight management programme. Second, the analysis aims to quantify the potential economic gains resulting from changes observed, providing a data-driven projection of the broader population-level benefits of digital-first GLP-1 interventions. Thirdly, the analysis aims to assess changes in use of health care services after 12 months in Oviva's digital Tier-3 weight management programme, specifically looking at self-reported GP and hospital visits (both virtual and in-person). Across all outcomes, we assess the extent to which changes are driven by other variables, such as patient engagement with the Oviva app, demographic variables or weight loss.

Study design

Oviva's digital Tier-3 weight management programme integrates weight loss medications with clinical behavioural support. The service is delivered via the Oviva app, which serves as the primary interface for patient-clinician interaction and monitoring. Key components include:

• Pharmacological intervention: Prescription, onboarding and titration of GLP-1 receptor agonists (e.g., Wegovy/Semaglutide), managed by a multidisciplinary clinical team.
• Remote specialist coaching: Patients are assigned a personal health coach (typically a specialist dietitian or weight management practitioner) for one-to-one support via secure in-app messaging and video consultations.
• Digital self-monitoring: Users utilise the app to track weight, nutritional intake, physical activity, and medication adherence. This real-time data allows clinicians to provide personalised feedback and intervene when progress stalls.
• Evidence-based curriculum: Access to a library of structured learning modules focused on cognitive behavioural therapy (CBT) techniques, nutrition education, and sustainable lifestyle changes to prevent weight regain.

Research design

This analysis is a longitudinal cohort study, meaning the same participants were followed over time and surveyed at baseline (just before starting the programme) and again 12-months later. Figure 2 summarises the study timeline.

Participants: eligibility for inclusion in the analysis

This analysis involves a subsample of the total number of individuals that Oviva treats. Since 2018, Oviva has treated 37,000 NHS UK Tier-3 patients. Participants included in this analysis must have been referred via the NHS to Oviva Tier-3 digital weight management programme and begun treatment no later than March 2025. Included participants must have agreed to continuous monitoring of weight and Oviva app usage, as well as provided consent for data to be used for research purposes. The analysis included participants that completed a baseline survey by March 2025 and a follow-up survey 12 months later.

The analysis includes a sample of approximately 2,000 participants from the Oviva Tier-3 digital weight management programme, representing roughly 50% of the eligible patients who completed the baseline survey but not the 12-month milestone survey.

Outcomes of interest

The key question of interest was how the following outcomes changed after 12 months of participation in the digital Tier-3 weight management programme:

• Employment status: Individuals were asked their employment status. Individuals could answer: employed full-time, employed part-time, unemployed, retired, carer or stay at home parent, self-employed, full time education.
• Sickness days: individuals were asked for self reported sick days over the last 3 months. Individuals could answer: 0, 1, 2, 3, 4 or 5 or more sick days.
• Health service use: participants were asked about their use of four appointment types (face-to-face and virtual GP appointments, as well as face-to-face and virtual hospital appointments) over the last three months. Individuals could answer: 0, 1, 2, 3, 4 or 5 or more appointments.

The following measures were also taken to better understand what factors influenced any identified changes (i.e. covariates) over the 12 month period:

• Clinical response: weight loss (absolute and % change) over 12 months.
• Engagement with Oviva app: number of activity logs, including weight measurements and physical activity entries, summed from baseline to 12 months; and total minutes spent on learning content over 12 months.
• Baseline characteristics: IMD decile, age, gender, ethnicity, baseline weight and baseline BMI.

What is a covariate?

A covariate is a secondary variable that might influence the outcome of interest. It can be viewed as a background factor - it is not the main thing under examination but it has the potential to skew results if they are not statistically accounted for.

Results output

For most analyses, the regression output is an Odds Ratio (OR).

Key Findings

Was the programme clinically effective?

Yes. The sample of approximately 2,000 patients lost an average of 17% of their body weight over the 12 month study period. This is similar to weight loss reported in clinical trials of comparable weight loss medications.

Did self-reported sickness change over the 12-month study period?

Employed participants had 42% lower odds in reporting a higher number of sickness absence days over the past 3 months (OR = 0.58, 95% CI 0.48 - 0.70, p< 0.001) at 12-month follow-up (Figure 3). This finding is statistically significant.

The reduction in self-reported sickness days varied among participants. Figure 3 shows that participants with lower BMIs generally exhibited a greater percentage change in sick days. Additionally, reduction in sickness absence at follow-up was more likely among participants who reported the highest number of sick days at baseline compared to those with lower baseline absence.

App engagement, weight loss, and baseline characteristics did not have a statistically significant association with self-reported sickness absence across the survey period.

What is the economic benefit of changes in self-reported sickness absence?

In the next phase of analysis, the aim was to estimate the potential economic benefit of changes in self reported sickness absence. For this exploratory analysis we assume that changes in self reported absence is a result of participating in a digital-first weight loss programme akin to that delivered by Oviva. A statistical model was used to scale these individual findings to the different scenarios. By converting reported reductions in sick leave into monetary value using the UK's median annual wage, we estimated the potential economic return on investment. Findings are presented for the three scenarios introduced in the Analytical Approach section.

These savings are a small proportion of the total costs of obesity as the NHS rollout includes only ~9% of the total population currently living with obesity.

Did employment status change over the 12 month study period?

No statistically significant changes were observed in employment status; however, the following descriptive changes were observed. The employment rates across the sample (including full-time and part-time) saw a slight dip from 60% at baseline to 58% after 12 months. The proportion of participants who were unemployed rose from 12% at baseline to 17% after 12 months. An unambiguous explanation of this change is not possible with the used research design, however this change may reflect wider economic developments in the UK. This reflects a broader national trend as the UK has recently experienced a general rise in unemployment rates (Labour Market Overview, 2026).

Did use of health services change over the 12 month study period?

There was a statistically significant reduction in self-reported healthcare visits in the last 3 months when comparing the baseline and 12- month surveys, across four appointment types. Compared to the preceding 3 months, at follow-up participants were approximately:

• 71% lower odds of reporting a face-to-face GP appointment at 12 months than at baseline (OR 0.29, 95% CI 0.26 – 0.33, p < 0.0001).
• 74% lower odds of reporting a remote GP appointment at 12 months than at baseline (OR 0.26, 95% CI 0.23 - 0.30, p < 0.0001).
• 48% lower odds of reporting a face-to-face hospital appointment at 12 months than at baseline (OR 0.52, 95% CI 0.45 - 0.60, p < 0.0001).
• 45% lower odds of reporting a remote hospital appointment at 12 months than at baseline (OR 0.29, 95% CI 0.47 - 0.66, p < 0.0001).

For the ~2,000 participants included in this analysis, this reduction in health service use equates to approximately £200,000 savings over 3 months. It was not reported whether the reported appointments were self funded (private) or NHS appointments.

Given our study sample accounts for only 0.1% of the planned 1.6m NHS rollout, if the same reduction was observed at scale, it is likely to result in meaningful cost savings related to healthcare utilisation. It is not clear how this would scale to 1.6 million people, given the difference a wider sample would have with regards to baseline BMI and healthcare use. However, to take a conservative estimate and assume reductions in appointments at half the rate observed in these analyses would result in about £80 million in cost savings for 1.6 million people.

Analytical Approach

Analyses for primary outcomes: changes in employment, sickness absence and health service use.

Oviva conducted the analysis of changes in self-reported sickness days, health service use and employment status over 12 months.

Representativeness of participants: The analysis was conducted on data collected from participants who completed surveys at baseline and at follow-up. 53% of participants who completed baseline surveys did not complete follow-up surveys and they are not included in the analyses. We compared the characteristics of participants included in this analysis with a representative sample of individuals living with obesity (using Health Survey for England 2024 data). Participants included in this analysis in this analysis were more likely to be female and living in less deprived areas of England. Oviva did not select specific groups to complete the survey; we cannot confirm statistically significant differences between those who completed the survey and those who did not.

Comparing averages at baseline and follow-up: To assess the change in the key outcomes over time, average scores from baseline survey responses were compared to those reported after 12 months. The appropriate statistical tests were selected based on the characteristics of the specific outcome measure (e.g. paired t-test for numerical scales, Wilcoxon signed-rank test for ordinal scales).

Accounting for background factors: To account for covariates and improve precision, primary endpoints were analysed using regression models. A multivariable logistic regression model was fitted to examine the association between covariates and the likelihood of improvement (defined as improved vs. not improved).

Analyses for estimating the economic benefits

Nesta led the analysis for estimating per-person and extrapolated potential economic gains derived from the observed reduction in sickness absence.

The baseline cost of untreated obesity was established using figures from the Frontier Economics report. To determine the cost of treated obesity, these baselines were adjusted by the improvements observed in Oviva's baseline and 12-month survey. The reduction in sick days was monetised using the UK's median annual wage[^4] and assuming a standard working year of 250 days to calculate the potential economic gain per-person. The analysis was segmented by obesity category (Class I/II vs. Class III)[^3] and gender to provide a range of potential economic gains per-person.

To capture the potential aggregate impact, these per-person gains were scaled across three distinct populations herein referred to as scenarios. Scenario 1 reflects the potential economic impact if the results observed are scaled to the entire Oviva Tier 3 cohort of approximately 37,000 patients. Scenario 2 expands this to the estimated 80,000[^5] NHS patients currently receiving weight loss treatments. Finally, Scenario 3 projects the benefits of the planned NHS rollout of tirzepatide, which targets 1.6 million eligible patients over 12 years.

In the model, we used the findings of the survey analyses (where participants were prescribed semaglutide) as a proxy for other similar weight loss medications currently available on the NHS (i.e. tirzepatide). Given the shared mechanism and broadly comparable efficacy for weight loss, it was assumed the findings of the primary outcomes would be applicable.

Limitations

While this report provides significant real-world evidence on the economic impact of Oviva Tier 3 programme, several limitations should be considered when interpreting the findings. First, as a longitudinal cohort study without a control group, the observed changes should be interpreted as associations rather than evidence of causation, meaning other factors may have influenced the outcomes.

Second, the generalisability of the findings is limited because the study participants, who were drawn from those completing both baseline and follow-up surveys (excluding 53% of the original sample), were more likely to be female and living in less deprived areas than the broader obese population. While this reflects common trends in voluntary weight-management enrollment, it limits the precision of our macro-economic extrapolations. Since labour market participation and healthcare utilisation is likely to vary by gender, having mostly female participants means our findings will not be representative of the broader obese population.

Third, due to data availability, the economic scope excludes other relevant expenditures, such as the social care and obesity-related treatment costs referenced by Frontier Economics and Nesta. Furthermore, the survey question design capped healthcare usage and sick days at '5+'. In our calculations, all '5+' responses were treated as 5. Consequently, this likely underestimates the actual figures for participants who experienced more than five events

Finally, other studies show that there is strong evidence that weight is regained following the cessation of weight loss medications. Since the analysis is based on a 12-month period, the projected economic gains should be considered exploratory and representative of active treatment effects, as the long-term sustainability of improvements after treatment cessation remains a risk.

Conclusions

The findings from this work suggest that the value of weight loss medications when delivered as part of a digital clinical service extends beyond clinical weight loss, associated with a drop in the number of sick days reported and reduced use of health services. These results suggest that patients are not only more present at work, but that these interventions also have the potential to free up capacity within the currently overstretched NHS.

For national policy, the primary implication is that the high cost of these medications could be partially offset by measurable economic returns linked to reduced workforce absenteeism. By shifting the focus from purely clinical weight loss to these broader outcomes, policymakers can build a more robust case for investment over time periods relevant to the government's 'growth mission'. Further evidence is needed to evaluate the long-term sustainability of these impacts given the 12 month time period of this study.

The consistency of these results across all demographic and socioeconomic groups underscores the necessity of broad NHS access. Currently, the private market is skewed toward affluent individuals with lower clinical needs. Without a robust NHS rollout, these interventions risk widening existing health inequalities rather than narrowing them.

Presently, it is estimated that only ~9% of people currently living with obesity will be the opportunity to access weight loss medications and treatment free of charge on the NHS over the next 12 years, and that even this ambition may be unachievable under the current trajectory. To address this gap in access for those with highest clinical need, and maximise the potential clinical, economic, and health system benefits of these innovations, there is a clear need to deliver on existing commitments, consider the case for a faster and wider rollout given additional benefits and regularly re-evaluate cost-effectiveness as evidence on wider benefits emerges. However, these clinical interventions must be viewed as one part of a comprehensive national strategy that acknowledges and manages obesity as a chronic, relapsing condition.

To achieve a sustainable and equitable reduction in obesity, we would like to see expanded weight loss medication access alongside the ongoing and critical need to improve the food environment through large-scale, mandatory government intervention.

Endnotes

1. This calculation is based on the NHS target of 1.6 million individuals relative to the 18.1 million adults living with obesity in the UK as identified in: Frontier Economics, The economic and productivity costs of obesity and overweight in the UK (2024).
2. Assumes all appointments are within the NHS; unit costs derived from Kent Academic Repository for Unit Costs for Health and Social Care. Costs were not available for remote GP visits. See technical appendix for full details.
3. Note: Obesity classification is based on NICE guidance (last revised in September 2025):
   • Overweight: BMI of 25–29.9 kg/m²
   • Class I: BMI of 30–34.9 kg/m²
   • Class II: BMI of 35–39.9 kg/m²
   • Class III: BMI of 40 kg/m² or more
4. Based on the Nesta/Frontier Economics report, the 2025 median wage (£31,956) was adjusted to 2026 levels using the OBR's 3.4% inflation rate
5. Based on the estimated 1.6 million GLP-1 users in 2025, a 95% private practice rate was applied to derive a 5% NHS utilisation baseline, resulting in an estimated cohort of 80,000 current NHS patients

All data is correct as of April 2026

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