Industries
- survey
- 9,097 respondents — industry cuts use the 8,400+ rows with a non-blank industry answer
- IT/SaaS sleeps best, EdTech worst — against the stereotype
- IT and manufacturing move most; EdTech moves least
- BFSI drinks and smokes the most
- EdTech is the most stressed large industry
- IT/SaaS reports the fewest chronic conditions — and it isn't just youth
- Health screening reaches almost no one outside manufacturing
- Therapy use is rare everywhere, lowest in the field industries
- What the industry data can and cannot say
Key takeaways
- IT/SaaS is not the unhealthiest industry — it's among the healthiest on most behavioural measures. Software workers sleep best (27.6% short sleep), move most (lowest zero-exercise at 26.9%), and self-report the fewest chronic conditions of any major industry (19.4%), against the workaholic-tech stereotype.
- EdTech/Education is the consistent worst performer. It tops short sleep (38.8%), zero exercise (38.6%), high stress (47.8%) among the large industries, and self-reported chronic conditions (35.0%).
- The IT advantage survives an age control. Among under-35s only — stripping out IT's younger workforce — software still posts one of the lowest chronic-condition rates (15.7%), so the finding is not simply that tech is young.
- BFSI is the substance industry. Banking and financial services report the highest alcohol use (44.6%) and nicotine use (21.4%) of any large sector — the client-entertainment signal that replicates from WHI 2025.
- Company health screening reaches almost no one outside manufacturing. Only manufacturing breaks 15% on employer-organised health camps (17.5%); in BFSI, healthcare, e-commerce, and media it sits below 9%.
- Half of e-commerce and logistics workers took no preventive action at all in the past year — no check-up, no diagnostic, no camp — the widest care-seeking gap in the survey.
The industry most associated with overwork is, in WHI 2026, one of the healthiest sectors on nearly every behaviour the survey measures. Of 2,807 IT/Software/SaaS respondents who answered the sleep question, 27.6% sleep under six hours — the lowest short-sleep rate of any major industry, three points below the 30.7% survey average. Software also posts the lowest zero-exercise rate and the fewest self-reported chronic conditions in the sample. The "burnt-out coder" is a durable cultural image; in this dataset it is not where the worst numbers live.
One feature of the sample has to be stated first. The survey skews heavily toward software: IT/SaaS is 36.3% of all respondents, larger than the next four industries combined. That reflects Loop's client book — India's organised group-insurance market is concentrated in technology and GCCs — not the national workforce, which is overwhelmingly informal. The comparisons below are between salaried, insured, urban professionals in each sector, not a portrait of the Indian labour force.
| Industry | Share of respondents | n |
|---|---|---|
| IT / Software / SaaS | 36.3% | 3,084 |
| Other | 13.7% | 1,166 |
| Healthcare | 8.2% | 697 |
| BFSI (Banking, Fintech, Insurance) | 8.0% | 682 |
| Manufacturing | 6.9% | 588 |
| EdTech / Education | 6.1% | 521 |
| E-commerce / Retail | 4.1% | 346 |
| Real Estate / Construction | 2.8% | 238 |
| Consulting | 2.2% | 189 |
| Logistics / Supply Chain | 2.2% | 187 |
| Hospitality / Travel | 1.8% | 157 |
| NGO / Non-Profit | 1.8% | 149 |
More than a third of the sample writes software
Share of survey respondents by industry — a feature of Loop's client book, not the national workforce
India's organised group-insurance market concentrates in technology and GCCs. These are salaried, insured, urban professionals — not a portrait of the (overwhelmingly informal) Indian labour force.
IT/SaaS sleeps best, EdTech worst — against the stereotype#
Short sleep — under six hours a night — is the cleanest single behavioural marker the survey carries, and it sorts the industries in an order most readers would not predict.
| Industry | Sample | Short sleep (<6 hrs) |
|---|---|---|
| EdTech / Education | 482 | 38.8% |
| Logistics / Supply Chain | 155 | 35.5% |
| Healthcare | 630 | 33.0% |
| BFSI | 607 | 32.8% |
| FMCG | 107 | 31.8% |
| E-commerce / Retail | 292 | 30.8% |
| Manufacturing | 519 | 30.4% |
| Consulting | 173 | 29.5% |
| Media / Entertainment | 129 | 29.5% |
| Real Estate / Construction | 204 | 28.9% |
| IT / Software / SaaS | 2,807 | 27.6% |
IT/SaaS sleeps best, EdTech worst — against the stereotype
Share sleeping under six hours a night, by industry
┄ Survey average — 30.7%
Values in %EdTech sits eleven points above IT/SaaS — an older cohort and earlier classroom starts against tech's younger workforce and the highest hybrid rates of any major industry.
EdTech sits eleven points above IT/SaaS. Two structural features fit the gap. EdTech skews older — a median age of 34 against IT's 30 — and the survey's sleep curve worsens after 40. And education's working day starts earlier: classroom and tutoring schedules pull the alarm forward in a way a 10am standup does not. IT's protection runs the other way — a younger cohort, and the highest hybrid and work-from-home rates of any major industry, which protect both the evening and the morning recovery window. The Sleep page reports the same direction from the other side: short sleep is the strongest single behavioural marker in the survey, and the Work Model page finds hybrid — not fully remote — the best-sleeping arrangement of the three.
IT and manufacturing move most; EdTech moves least#
Zero exercise — no day in a typical week with thirty minutes of activity — tracks the sleep ranking closely, and puts the same two industries at the poles.
| Industry | Sample | Zero exercise |
|---|---|---|
| EdTech / Education | 474 | 38.6% |
| Logistics / Supply Chain | 155 | 37.4% |
| Media / Entertainment | 129 | 37.2% |
| Hospitality / Travel | 129 | 34.9% |
| E-commerce / Retail | 287 | 33.8% |
| FMCG | 106 | 33.0% |
| Real Estate / Construction | 203 | 32.5% |
| Consulting | 172 | 32.0% |
| Healthcare | 627 | 30.5% |
| BFSI | 597 | 29.6% |
| Manufacturing | 519 | 27.9% |
| IT / Software / SaaS | 2,789 | 26.9% |
IT and manufacturing move most; EdTech moves least
Share reporting zero days a week with thirty minutes of activity, by industry
The two lowest bars get there by opposite routes — software through autonomy over the day, manufacturing through the physical work itself.
IT and manufacturing reach the same destination by opposite routes. Software gets there through autonomy over the day — the flexibility to fit a walk or gym session around a calendar the worker partly controls. Manufacturing gets there through the job itself; the work involves movement a desk job does not. EdTech is again at the bottom: an older, more sedentary workforce that combines a desk with an early start.
BFSI drinks and smokes the most#
Substance use is where the industry stereotypes mostly hold. BFSI — banking, fintech, insurance — leads both alcohol and nicotine among the large industries, the client-entertainment-and-targets signal that WHI 2025 also found.
| Industry | Sample | Any alcohol use |
|---|---|---|
| Real Estate / Construction* | 198 | 53.5% |
| Media / Entertainment* | 125 | 49.6% |
| Consulting | 168 | 43.5% |
| E-commerce / Retail | 273 | 43.2% |
| BFSI | 579 | 44.6% |
| Manufacturing | 494 | 38.3% |
| Healthcare | 608 | 37.0% |
| IT / Software / SaaS | 2,703 | 35.3% |
| EdTech / Education | 465 | 31.8% |
| NGO / Non-Profit | 135 | 25.2% |
BFSI is the largest industry above the 40% line on alcohol
Share reporting any alcohol use, by industry — small-sample sectors shown faded
┄ 40% line
Values in %*Real estate (n = 198) and media (n = 125) clear the 100-respondent floor but sit on small samples; read directionally. Among reliable samples, BFSI is the clearest reading: 44.6% vs 35.3% in IT.
Among the industries with reliable samples, BFSI is the clearest reading: 44.6% report drinking, against 35.3% in IT. Nicotine sorts the same way.
| Industry | Sample | Nicotine use |
|---|---|---|
| E-commerce / Retail | 272 | 25.4% |
| Real Estate / Construction | 197 | 23.4% |
| BFSI | 576 | 21.4% |
| Healthcare | 607 | 19.9% |
| Manufacturing | 489 | 19.2% |
| IT / Software / SaaS | 2,694 | 15.4% |
| EdTech / Education | 461 | 12.6% |
| NGO / Non-Profit | 134 | 11.2% |
Nicotine sorts the same way — BFSI high, IT and EdTech low
Share reporting nicotine use, by industry — rows ordered to match the alcohol chart above
Read alongside the alcohol chart: BFSI sits high on both substances; IT and EdTech sit low on both. The client-entertainment signal replicates from WHI 2025.
BFSI's profile — high on both alcohol and nicotine, in a sector with above-average stress and a male-skewed senior layer — is the most coherent industry-culture signal in the survey. Drinking and smoking are normalised as professional tools in client-facing finance in a way they are not in software. EdTech drinks and smokes least; whatever else burdens that workforce, substance use is not it.
EdTech is the most stressed large industry#
High stress — a self-rating of 7 or above on a 10-point scale for the past week — is widespread across every industry, but EdTech sits clearly above the rest of the large sectors.
| Industry | Sample | High stress (7–10/10) |
|---|---|---|
| NGO / Non-Profit* | 138 | 53.6% |
| EdTech / Education | 467 | 47.8% |
| FMCG* | 103 | 47.6% |
| Energy / Utilities* | 76 | 44.7% |
| BFSI | 586 | 44.2% |
| Hospitality / Travel* | 128 | 43.8% |
| Consulting | 170 | 42.9% |
| Healthcare | 616 | 41.2% |
| Logistics / Supply Chain | 146 | 40.4% |
| Manufacturing | 504 | 39.1% |
| IT / Software / SaaS | 2,735 | 38.4% |
| E-commerce / Retail | 279 | 37.6% |
| Real Estate / Construction | 200 | 34.5% |
EdTech is the most stressed large industry
Share rating past-week stress 7–10 out of 10, by industry
┄ Survey average — 40.4%
Values in %*NGO (n = 138), FMCG (n = 103), energy (n = 76) and hospitality (n = 128) clear the floor but on samples too small to rank confidently; read directionally. The reliable reading is among industries above ~450 respondents. The WHI 2025 healthcare figure (57.1%, n = 346) is small-sample noise, not a year-on-year deterioration against the 41.2% here.
The healthcare reading inverts WHI 2025. Last year healthcare topped the stress ranking at 57.1%; this year it sits mid-pack at 41.2%. The earlier number rode on a small sample (346 respondents) and is best read as noise. On the larger 2026 base, the highest-stress large industry is EdTech, and the pattern that holds across both years is that stress is high everywhere — no major industry sits below 37%. The Stress page carries the 40.4% workforce-wide figure these industry rates sit around.
IT/SaaS reports the fewest chronic conditions — and it isn't just youth#
The behavioural cuts above describe how people in each industry live. The self-reported chronic-condition data describes where that living has already landed. Here IT/SaaS posts the lowest burden of any large industry, and EdTech the highest.
| Industry | Sample | Any chronic condition (self-report) |
|---|---|---|
| EdTech / Education | 389 | 35.0% |
| Real Estate / Construction | 168 | 31.0% |
| NGO / Non-Profit | 110 | 30.9% |
| Healthcare | 533 | 25.3% |
| Manufacturing | 403 | 25.1% |
| BFSI | 474 | 23.6% |
| E-commerce / Retail | 222 | 21.6% |
| IT / Software / SaaS | 2,323 | 19.4% |
| Consulting | 148 | 14.9% |
A 15-point spread separates EdTech from IT/SaaS on chronic disease
Share self-reporting any chronic condition, by industry — all ages
Self-reported diagnosis undercounts true prevalence; the industry ordering is the finding, not the absolute rates. The gap between detected and reported disease is likely widest in the industries that screen least.
The obvious objection is age. IT's workforce is the youngest of any major industry — a median of 30 against EdTech's 34 — and chronic conditions accumulate with age, so a younger industry should look healthier whether or not anything about the work protects it. The cut controls for it.
| Industry (under 35 only) | Sample | Any chronic condition |
|---|---|---|
| Healthcare | 371 | 22.4% |
| EdTech / Education | 196 | 22.4% |
| BFSI | 314 | 18.5% |
| Real Estate / Construction | 82 | 18.3% |
| Manufacturing | 236 | 17.8% |
| IT / Software / SaaS | 1,702 | 15.7% |
| E-commerce / Retail | 144 | 13.9% |
| Consulting | 111 | 12.6% |
The IT advantage survives the age control
Share self-reporting any chronic condition, under-35s only — same layout as above
Restricted to under-35s, the IT-low / EdTech-high ordering holds: software still posts 15.7% while EdTech and healthcare top the large industries at 22.4%. The finding is not simply that tech is young.
Restricted to under-35s, the ordering holds. IT/SaaS still sits near the bottom at 15.7%; EdTech and healthcare still top the large industries at 22.4%. The IT advantage is not an artefact of a young workforce — it persists when the youngest cohort of every industry is compared like for like. The self-reported diabetes cut points the same way: IT/SaaS at 5.0% sits below EdTech (8.5%), real estate (12.4%), and manufacturing (7.5%).
Health screening reaches almost no one outside manufacturing#
The survey asked what people had actually done about their health in the past year. The care-seeking gap between industries is as wide as any behavioural gap on the page — and it runs in a direction that should worry the sectors at the bottom.
| Industry | Routine check-up | Full-body diagnostic | Company health camp | No action at all |
|---|---|---|---|---|
| IT / Software / SaaS | 25.4% | 26.6% | 11.4% | 41.1% |
| BFSI | 25.4% | 23.0% | 8.7% | 44.0% |
| Healthcare | 24.3% | 26.1% | 8.1% | 41.5% |
| Manufacturing | 24.0% | 20.8% | 17.5% | 41.5% |
| EdTech / Education | 22.2% | 24.9% | 11.5% | 37.7% |
| Real Estate / Construction | 26.7% | 27.2% | 13.6% | 35.1% |
| Consulting | 20.7% | 34.1% | 7.9% | 35.4% |
| E-commerce / Retail | 21.7% | 17.9% | 6.8% | 54.0% |
| Logistics / Supply Chain | 20.4% | 16.9% | 7.7% | 53.5% |
Health screening reaches almost no one outside manufacturing
Preventive action taken in the past year, by industry — “no action at all” is the warning measure
Manufacturing is the only sector where employer health camps reach more than one in seven workers (17.5%). More than half of e-commerce (54.0%) and logistics (53.5%) workers took no preventive action of any kind.
Two readings stand out. The first is that company-organised screening barely exists outside the factory floor. Manufacturing is the only sector where employer health camps reach more than one in seven workers — a legacy of occupational-health regulation and physical worksites with on-premise medical infrastructure. In the desk industries, fewer than one in eight touched an employer screening programme; in healthcare, BFSI, and e-commerce, fewer than one in eleven. The benefit exists on paper at most of these employers; it is not reaching the body.
The second is the care-seeking floor. More than half of e-commerce and logistics workers took no preventive action of any kind in the past year — no check-up, no diagnostic, no camp. These are also among the higher-stress, higher-substance, shorter-sleeping sectors. The industries whose behaviour suggests they most need a check-up are the least likely to get one — the same income-gated screening gap the Preventive Care page traces from 15.6% at the lowest earners to 54.3% at the highest, surfacing here as an industry pattern.
Therapy use is rare everywhere, lowest in the field industries#
Mental-health care-seeking is low across the board and follows the same fault line as physical screening: it is concentrated in the desk-and-degree industries and thin in the field-and-shift ones.
| Industry | Sample | Ever taken therapy |
|---|---|---|
| NGO / Non-Profit* | 138 | 21.7% |
| EdTech / Education | 471 | 13.8% |
| Healthcare | 617 | 13.1% |
| Consulting | 170 | 12.9% |
| BFSI | 588 | 11.4% |
| IT / Software / SaaS | 2,748 | 9.4% |
| Manufacturing | 507 | 8.9% |
| Real Estate / Construction | 200 | 8.0% |
| Logistics / Supply Chain | 151 | 7.9% |
| E-commerce / Retail | 285 | 7.4% |
| Hospitality / Travel | 128 | 5.5% |
Therapy use is rare everywhere, lowest in the field industries
Share who have ever taken therapy, by industry
*NGO on a small sample (n = 138); read directionally. No industry clears 22% and most sit below 12% — care-seeking, mental and physical, splits the workforce along the same desk-vs-field line.
EdTech and healthcare — the two industries carrying the heaviest chronic and stress load among the young — also report the highest therapy use among the large sectors. That is the healthier reading of an otherwise difficult picture: the sectors under the most strain are at least the most likely to seek help. Hospitality, logistics, and e-commerce sit at the bottom on therapy exactly as they do on physical screening. Care-seeking, mental and physical, is a single behaviour in this data, and it splits the workforce along the same line.
What the industry data can and cannot say#
Three things this page establishes, and one large thing it cannot.
- The industry most associated with overwork — IT/SaaS — is among the healthiest in this sample on sleep, movement, and self-reported chronic disease, and the advantage survives an age control.
- EdTech/Education is the most consistent underperformer across behaviour and outcomes; healthcare and the field industries (logistics, e-commerce, hospitality) carry the worst care-seeking gaps.
- Employer health screening is, outside manufacturing, almost absent — and weakest in the very sectors whose behaviour suggests they need it most.
References
- 1ICMR-INDIAB Collaborative Study Group. Metabolic non-communicable disease health report of India: the ICMR-INDIAB national cross-sectional study. The Lancet Diabetes & Endocrinology 11, 474–489 (2023). https://doi.org/10.1016/S2213-8587(23)00119-5
- 2Virtanen, M., Jokela, M., Madsen, I.E.H. et al. Long working hours and depressive symptoms: systematic review and meta-analysis of published studies and unpublished individual participant data. Scandinavian Journal of Work, Environment & Health 44, 239–250 (2018). https://doi.org/10.5271/sjweh.3712
- 3Kivimäki, M., Nyberg, S.T., Batty, G.D. et al. Job strain as a risk factor for coronary heart disease: a collaborative meta-analysis of individual participant data. The Lancet 380, 1491–1497 (2012). https://doi.org/10.1016/S0140-6736(12)60994-5
- 4Marmot, M.G., Stansfeld, S., Patel, C. et al. Health inequalities among British civil servants: the Whitehall II study. The Lancet 337, 1387–1393 (1991). https://doi.org/10.1016/0140-6736(91)93068-K