LoopWHI ’26

Industries

survey
9,097 respondents — industry cuts use the 8,400+ rows with a non-blank industry answer

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

IT / Software / SaaS
n = 3,084
36.3%
Other
n = 1,166
13.7%
Healthcare
n = 697
8.2%
BFSI (Banking, Fintech, Insurance)
n = 682
8.0%
Manufacturing
n = 588
6.9%
EdTech / Education
n = 521
6.1%
E-commerce / Retail
n = 346
4.1%
Real Estate / Construction
n = 238
2.8%
Consulting
n = 189
2.2%
Logistics / Supply Chain
n = 187
2.2%
Hospitality / Travel
n = 157
1.8%
NGO / Non-Profit
n = 149
1.8%
Values in %

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

EdTech / Education
n = 482
38.8%
Logistics / Supply Chain
n = 155
35.5%
Healthcare
n = 630
33.0%
BFSI
n = 607
32.8%
FMCG
n = 107
31.8%
E-commerce / Retail
n = 292
30.8%
Manufacturing
n = 519
30.4%
Consulting
n = 173
29.5%
Media / Entertainment
n = 129
29.5%
Real Estate / Construction
n = 204
28.9%
IT / Software / SaaS
n = 2,807
27.6%

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

EdTech / Education
n = 474
38.6%
Logistics / Supply Chain
n = 155
37.4%
Media / Entertainment
n = 129
37.2%
Hospitality / Travel
n = 129
34.9%
E-commerce / Retail
n = 287
33.8%
FMCG
n = 106
33.0%
Real Estate / Construction
n = 203
32.5%
Consulting
n = 172
32.0%
Healthcare
n = 627
30.5%
BFSI
n = 597
29.6%
Manufacturing
n = 519 · physical work
27.9%
IT / Software / SaaS
n = 2,789 · flexibility
26.9%
Values in %

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

Real Estate / Construction*
n = 198 · small sample
53.5%
Media / Entertainment*
n = 125 · small sample
49.6%
BFSI
n = 579
44.6%
Consulting
n = 168
43.5%
E-commerce / Retail
n = 273
43.2%
Manufacturing
n = 494
38.3%
Healthcare
n = 608
37.0%
IT / Software / SaaS
n = 2,703
35.3%
EdTech / Education
n = 465
31.8%
NGO / Non-Profit
n = 135
25.2%

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

Real Estate / Construction
n = 197
23.4%
BFSI
n = 576
21.4%
E-commerce / Retail
n = 272
25.4%
Manufacturing
n = 489
19.2%
Healthcare
n = 607
19.9%
IT / Software / SaaS
n = 2,694
15.4%
EdTech / Education
n = 461
12.6%
NGO / Non-Profit
n = 134
11.2%
Values in %

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

NGO / Non-Profit*
n = 138 · small sample
53.6%
EdTech / Education
n = 467
47.8%
FMCG*
n = 103 · small sample
47.6%
Energy / Utilities*
n = 76 · small sample
44.7%
BFSI
n = 586
44.2%
Hospitality / Travel*
n = 128 · small sample
43.8%
Consulting
n = 170
42.9%
Healthcare
n = 616
41.2%
Logistics / Supply Chain
n = 146
40.4%
Manufacturing
n = 504
39.1%
IT / Software / SaaS
n = 2,735
38.4%
E-commerce / Retail
n = 279
37.6%
Real Estate / Construction
n = 200
34.5%

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

EdTech / Education
n = 389
35.0%
Real Estate / Construction
n = 168
31.0%
NGO / Non-Profit
n = 110
30.9%
Healthcare
n = 533
25.3%
Manufacturing
n = 403
25.1%
BFSI
n = 474
23.6%
E-commerce / Retail
n = 222
21.6%
IT / Software / SaaS
n = 2,323 · −15.6 pp vs EdTech
19.4%
Consulting
n = 148
14.9%
Values in %

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

Healthcare
n = 371
22.4%
EdTech / Education
n = 196
22.4%
BFSI
n = 314
18.5%
Real Estate / Construction
n = 82
18.3%
Manufacturing
n = 236
17.8%
IT / Software / SaaS
n = 1,702
15.7%
E-commerce / Retail
n = 144
13.9%
Consulting
n = 111
12.6%
Values in %

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

Routine check-upFull-body diagnosticCompany health campNo action at all

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 / Non-Profit*
n = 138 · small sample
21.7%
EdTech / Education
n = 471
13.8%
Healthcare
n = 617
13.1%
Consulting
n = 170
12.9%
BFSI
n = 588
11.4%
IT / Software / SaaS
n = 2,748
9.4%
Manufacturing
n = 507
8.9%
Real Estate / Construction
n = 200 · field
8.0%
Logistics / Supply Chain
n = 151 · field
7.9%
E-commerce / Retail
n = 285 · field
7.4%
Hospitality / Travel
n = 128 · field
5.5%
Values in %

*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

  1. 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
  2. 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
  3. 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
  4. 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