GLP-1 Economic Impact by Industry: The 2026 Data Roundup

GLP-1 medications have moved from a healthcare story to a business one. It's now showing up in earnings calls, trade press, and category-level forecasts across food service, apparel, CPG, alcohol, fitness, and beyond, and every industry is reading it differently, often with opposite conclusions from companies competing in the same category.

If you lead marketing, operations, or data strategy at a consumer-facing brand, you've likely seen a version of this stat already: a headline number from a research firm, an analyst note, or a competitor's earnings call, dropped into a slide deck as evidence that “something is happening.” What's harder to find is a single, credible view of how large this shift actually is, sized consistently across categories, not scattered across a dozen syndicated reports.

This roundup pulls together the most current, sourced figures across the industries most exposed to GLP-1-driven behavior change. Each section closes with the same question, because it's the one number can't answer on its own: is this happening to your customers specifically, or just to the category average?

Food Service & Restaurants

The clearest, most-cited data lives here. Dinner traffic among regular GLP-1 users has declined by roughly 6%, concentrated at fast food and casual dining, and snack and confectionery purchases in GLP-1 households are down an estimated 12%. J.P. Morgan projects the cumulative hit could reach $30–55 billion in annual food and beverage revenue by 2030–2034, industry-wide — a range wide enough that where a given operator falls within it is essentially unknowable from the outside.

Operators have largely responded the same way: marketing existing high-protein menu items harder, as seen with moves like El Pollo Loco's Protein Packed Menu push. It's a reasonable first move. It's cheap, fast, and low-risk, making it a prime target as the first lever every operator in the category pulls before considering anything structural. That's exactly what makes it a stopgap rather than a strategy: once every competitor has run the same protein-forward campaign, the tactic stops being a differentiator and starts being table stakes. None of the industry-level figures above tell an individual restaurant group which of its own locations, dayparts, or guest segments are actually driving the decline, whether the protein-forward marketing push is working on the customers it's meant for, or when it will stop working.

There's also a second-order effect worth naming: the snack and confectionery decline (down ~12% in GLP-1 households) tends to get less attention than the dinner-traffic number, but it points to a different kind of exposure — impulse and add-on revenue, not just core visit frequency. A brand that's only watching traffic could miss a meaningful basket-size erosion happening underneath a stable visit count.

The gap: menu mix and reformulation decisions are made far slower than the underlying shift moves. By the time traffic data confirms a trend at the category level, it's already showing up on a P&L. Standard POS, ERP, and BI stacks report what sold, not why it stopped selling, or which customers stopped buying it.

Apparel & Retail

Apparel is absorbing this shift on a delay, and unevenly. Estimates put up to $5 billion in U.S. apparel margin at risk, with as many as 400 million units potentially misaligned to demand by 2027. Target has reported extended-size demand down 37% year-over-year. The impact is sharpest at plus-size specialists: Torrid reported a 14.3% year-over-year sales decline, and DXL attributed part of its own 6% decline to an estimated 25% of its customer base being on a GLP-1 medication and delaying purchases.

What makes apparel structurally different from food service is that this isn't one event. What the industry is experiencing are two waves, moving in opposite directions on different timelines. The first wave is a wardrobe-replacement revenue surge during active weight loss, as customers buy down through sizes; most brands are underestimating this as a near-term opportunity rather than treating it purely as risk. The second wave is a longer, structural shift in the size curve itself, playing out over multiple years, which is the piece most retail planning and buying teams are unprepared to forecast against. Brands that only track the second wave miss the revenue sitting in the first one.

There's a third, less-covered layer underneath both waves. ThredUp data shows plus-size resale volume up 6% year-over-year while small/medium resale volume fell 6% — the same disruption monetized twice, just not by the retailer that originated the customer relationship. Every one of those resale transactions represents a customer the original brand already had, transacting with someone else instead.

The gap: sizing and buying decisions are typically locked 6–9 months ahead of a selling season — far too slow to track a physiological trend moving in real time. Most retail CRM systems also have no way to distinguish a customer who's delaying a purchase from one who's left for good, which means the actual size of a brand's exposure (and its resale opportunity) is invisible until it shows up in a quarterly sales number.

CPG & Grocery

This is the category where the data itself is contested. Mondelez has stated it sees no measurable demand effect from GLP-1 adoption. PepsiCo, in the same reporting period, has been actively repositioning its portfolio toward smaller portions and functional formats. Independent estimates put category-wide CPG revenue impact at roughly $32 billion in 2024, rising toward $44–52 billion by 2026–2028.

Two major players in the same aisle, reading the same macro trend in opposite directions, is itself the finding: aggregate research can tell you the industry is affected. It can't tell you which read is correct for your specific brand and customer base. Both companies are large enough, and their portfolios diversified enough, that it's plausible both are right (about their own base) and still wrong as a general rule for anyone else in the category.

That's the trap in treating either company's position as a template. A mid-size CPG brand doesn't have Mondelez's or PepsiCo's category breadth to absorb a wrong bet across a full portfolio. Reformulating a full line on a hunch is expensive and slow to reverse; doing nothing while a real shift compounds is just as costly, only less visible until it's already lost share.

The gap: a CPG brand deciding whether to reformulate, resize, or hold steady is making a bet (i.e. reformulate everything, or do nothing) with no proprietary signal indicating whether its situation looks more like Mondelez's or PepsiCo's.

Alcohol & Beverage

Brown-Forman and Diageo have both named GLP-1 adoption a top-three structural threat to volume, in the same breath as cannabis substitution and Gen Z's lower baseline drinking rates. Unlike food service, alcohol has few compensating growth categories to offset the decline. For example, there's no equivalent of a “protein SKU” push to fall back on.

That also makes it the hardest attribution problem on this list. A given customer's declining purchase frequency could plausibly trace to any of the three causes, and most brands currently have no way to separate them at the individual level. That matters more here than it does in food service or apparel, because the right response to each cause is different: a Gen Z-driven decline calls for a long-term brand and positioning play; a cannabis-substitution decline calls for a category or occasion response; a GLP-1-driven decline calls for the same kind of segment-level detection and reformulation thinking playing out in CPG. Applying the wrong fix to the wrong cause wastes a marketing budget without moving the number that's actually declining.

The gap: without identity resolution or behavioral-pattern detection at the customer level, “GLP-1, cannabis, or Gen Z” stays a debate about the category, but never an answer for a specific account.

Fitness & Wellness

The data here points to a shift in intent rather than a decline in demand. Roughly 60% of GLP-1 users report exercising more, not less. What's changed is the goal: from calorie-burning toward muscle preservation and body composition, alongside rising interest in wearables-driven metabolic tracking (Whoop, Oura) and structured post-treatment maintenance programming.

Most fitness marketing and class programming is still built for the old intent (burn more, lose weight) and hasn't caught up to a member base that increasingly wants the opposite framing. That mismatch also spans a longer member lifecycle than most fitness brands are currently segmenting for. A member actively titrating on a GLP-1 has different needs than one who's reached a maintenance dose, and both look different again from someone who's discontinued and is trying to preserve results without the medication. Most membership and CRM systems still treat all three as one generic “weight loss” member.

The gap: undetected intent-shift is a data problem before it's a programming problem. Gyms and wellness brands need to know which members have shifted goals — and which are in a maintenance or post-discontinuation phase — before they can market or program to them correctly.

Marketing & Advertising

This is the thinnest data set on this list, and worth naming as such: early brand- and agency-side reports describe reduced response to food and impulse-purchase creative among GLP-1 users, but this is directional, not rigorously measured, unlike the food-service or apparel figures above. Several major CPG and retail brands are already shifting messaging away from abundance and impulse framing toward wellness and portion-consciousness anyway.

The gap: reframing brand messaging without segment-level detection risks alienating the customers who haven't actually shifted. The responsible move isn't to ignore a directional signal or to overreact to it — it's to test it against your own campaign data before committing a full creative strategy to it.

Adjacent: Commercial Real Estate & Employer Benefits

Two white-space categories are worth flagging even though they sit outside the core consumer-behavior story above. Commercial real estate owners with retail exposure — Macerich among them — are reporting GLP-1-driven shifts across food, fitness, and apparel tenants simultaneously, meaning operators are managing a multi-tenant version of the same demand shift retailers face individually, with no cross-tenant visibility to see it coming. Separately, employers and health plans are grappling with how to structure GLP-1 drug coverage — a benefits-data problem adjacent to, but distinct from, the consumer-behavior question this roundup otherwise covers.

The Pattern Across Every Industry

Read across all seven categories, the same structural problem repeats: the systems brands already have weren't built to answer this question. POS, ERP, BI dashboards, and CRM platforms report what happened in aggregate. None of them were designed to isolate a GLP-1-correlated behavior change from a price change, a competitive move, or ordinary seasonal variance — at the level of an individual customer, store, or SKU.

That's the piece every syndicated research report (such as those from Circana, McKinsey, Impact Analytics, and NielsenIQ) stops short of. They can size the trend at the market level. They can't tell you which of your customers are driving it, at what velocity, or what would re-engage them, because that answer doesn't live in a research subscription. It lives in your own data, if your data architecture is built to surface it.

How Stable Kernel Is Positioned to Help

Everything above is the kind of research a well-resourced team could assemble on its own: pull earnings calls, review analyst reports, and understand the macro trends shaping an industry. It's valuable context—but it still leaves one critical question unanswered:

Is this happening to your customers?

That's where Stable Kernel is different.

Rather than asking organizations to make strategic decisions based on industry averages, we help them understand how these trends are affecting their own customers, business, and market—before investing in major operational or product changes.

Our research approach is designed to move organizations from broad industry observations to evidence-based business decisions through three focused phases.

Phase 1: Business Discovery

Every engagement begins with a collaborative discovery session to understand your business, your customers, and the questions that matter most.

Together, we identify:

• The business decisions you're trying to make
• What customer and operational data already exists
• Where uncertainty or conflicting signals exist
• The hypotheses that need to be tested

The outcome is a focused research roadmap built around your business—not the industry average.

Phase 2: Customer Discovery

Next, we conduct a series of online, one-on-one in-depth interviews with the people who matter most—your customers, prospects, or other key stakeholders.

This qualitative phase helps uncover:

• How customers are actually thinking and behaving
• The motivations behind changing behaviors
• Emerging needs and unmet opportunities
• Language, emotions, and decision drivers that quantitative data alone can't explain

Rather than assuming why industry trends are occurring, we hear it directly from the people experiencing them.

Phase 3: Market Validation

Finally, we validate those findings through a robust quantitative online survey with a statistically reliable sample of your target audience.

This phase allows us to:

• Measure the prevalence of qualitative findings
• Confirm or disprove initial hypotheses
• Identify which customer segments are most affected
• Quantify business impact and market opportunity
• Prioritize actions based on evidence rather than assumptions

The result is a clear, data-driven understanding of what's happening in your market—and the confidence to act.

Where to Go From Here

Every figure in this roundup answers "How big is this, industry-wide?" None of them answer "Is this happening in my business, and which customers are driving it?"

That's exactly the question market research is designed to answer.

If you're wondering how GLP-1 adoption (or any other emerging trend) may be affecting your customers, we'd be happy to talk. Whether you're looking to validate a hypothesis, understand changing customer behavior, or quantify the business impact, we'd love to explore it with you.

Start the conversation by emailing Emily Creek at [email protected]

____________________________________________________________________________________________________________________________________________________________________________

Sources cited throughout: J.P. Morgan, Circana, ThredUp, Target, Torrid, DXL, Mondelez, PepsiCo, Brown-Forman, Diageo, Macerich, and independent CPG market estimates. Figures should be treated as directional where noted (Marketing & Advertising section) and refreshed quarterly as new earnings and research data become available.