Investment Manifesto | Kapil Khandelwal KK

Why are Indians Losing Sleep? How do We Regulate Sleep?

Why are Indians Losing Sleep

Introduction

There are various sleep guidelines for adults from various experts and institutions that vary from 7 to 9 hours per night, every night. However, as we will discuss here, this is not be adequately being followed and complied by individuals in India and around the world. There are several individual (such as personal, socio-demographic, lifestyle, health) and work related (psychosocial and job) factors that affects and inhibits regular sleep patterns of individuals (see Box).

Factors Affecting Sleep - Lifestyle and health factors — Factors Affecting Sleep – Lifestyle and health factors

Factors Affecting Sleep - Personal and socio-demographic factors — Factors Affecting Sleep – Personal and socio-demographic factors

Factors Affecting Sleep - Workplace psychosocial and job factors — Factors Affecting Sleep – Workplace psychosocial and job factors

In our 2024: Healthcare & Lifesciences Investment Manifesto – Top 40 Future Bets, our bet #39 discussed about Sleep Biology. See 2024 – India Healthcare And Life Sciences Investment Manifesto | Kapil Khandelwal KK for more details. We believed that The traditional “one-size-fits-all” approach to sleep is becoming obsolete and we need to reimagine solutions under “Sleep Biology” given that we all understand the consequences of lack of proper sleep. Our hunch was that Gen Z and Millennian in India are more sleep deprived. This has turned out to be true. Meta analysis of all the research papers on Indians sleep or lack of sleep patterns is in the Annexure 1. Moreover, the recent report from various and our inhouse analysis gives a very grim view of why Indians are losing sleep?

Indian Sleeping Statistics

The chart below summarises the impact of lack of sleep among Indians and some of the causes for it. We will discuss the impact of lack of sleep later.

India Macro Sleep Economics

Sleep deprivation significantly impacts India’s Human Capital Index (HCI). Chronic sleep deprivation can lead to reduced cognitive abilities, lower productivity, and increased absenteeism. These factors collectively diminish the overall quality of human capital, which is crucial for economic growth and development. The chart below shows the overall impact to GDP for various countries, including India:

Macro Sleep Economics (Impact on GDP due to Lack/Less Sleep)

India is at risk of losing of GDP, an opportunity cost, as a nation over losing sleep of its citizens and this will be a huge issue in the future.

How do We Regulate Sleep? The National Sleep Monitoring and Regulatory Authority (NSMRA)

Given the loss of sleep and India’s GDP, there is a need to set up a National Sleep Monitoring and Regulatory Authority (NSMRA). This Authority will be empowered to ensure that there is a proper and enabling environment to assure that the issues emerging out of lack of citizen’s sleep are mitigated. The Authority will align with various health and labour initiatives and regulations prevailing in India. Some of the objectives, though not exhaustive, of NSMRA would be:

Indian Citizen Lifestyle Ethos and Culture

Set a consistent wake-up time
Limit time spent in bed on activities other than sleeping
Do not stay in bed unless asleep
Limit the use of electronic devices before bedtime
Limit the consumption of substances which may impair sleep quality
Address stressful issues long before bedtime
Exercise and alignment with

Labour and Employment Laws Modifications

Recognise the importance of sleep and the employer’s role in its promotion
Commit to build a culture to helping employees achieve better sleep outcomes

Work Environment Regulatory Guidance and Monitoring

Minimise variability in working hours and maximize employees’ control
Discourage the extended use of electronic devices
Address physical workplace risk factors
Combat workplace psychosocial risks
Provide facilities and amenities that help employees with their sleep hygiene
Design and build brighter workspaces
Support health workers in providing sleep-related help
Encourage employers to pay attention to sleep issues
Make use of existing workspace mandates and their enforcement
Introduce later school starting times
Raise general awareness of the benefits of sleep

Let’s look forward to Healthy India and Wealthy (GDP Opportunity Cost Savings)

Annexure 1

Sr No.	Author	Study Design	Participants Group	Sample Size(n)	Age(Mean+SD) /Age Group	Assessment Tool	Sleep Disorder Addressed	JBI Score (0-10)
1	H. K. Aggarwal et al., 2017	Cross sectional study	CKD stage III to V patients	200	50.11+13.99	PSQI	Insomnia	7
2	S. Ahmad et al., 2013	Cross sectional study	Adults with CKD	104	54.17+12.96	ISI, STOP-BANG	Insomnia	9
3	Jain et al., 2017	Cross sectional study	Type-2 diabetes patients	50	48.25+19.05	ISI	Insomnia	7
4	Dahale et al., 2020	Multicentre cross sectional survey	Elderly patients attending PHCs	1574	68.6+6.3	ISI	Insomnia	8
5	Uvais et al., 2021	Cross sectional study	Nurse and other staff	347	29.12+6.85	ISI	Insomnia	7
6	Panda et al., 2012	Observational cross sectional study	Healthy subjects accompanying patients	1050	35.1+8.7	ESS, PSQI	RLS, Insomnia	9
7	Shivashankar et al., 2017	Cross sectional study	Healthy participants	16287	42.03+12.43	Sleep Habbits questionnaire, ESS	Insomnia, EDS	6
8	Katyayan et al., 2019	Cross sectional study	Healthy subjects	850	44.68+10.44	ESS, BQ, STOP BANG	Insomnia	8
9	Dewan et al., 2022	Questionnaire-based survey study	Dental students	1115	21+1.8	SLEEP-50 questionnaire (that had 50 questions)	OSA, Insomnia	6
10	Jain et al., 2020	Cross sectional study	Students University of Rajasthan and affiliated colleges	954	23.81+3.72	ISI	Insomnia	7
11	N. Kumar et al., 2022	Cross-sectional study	General People	1596	39.76+13.1	Standard questionnaire	RLS, Insomnia	4
12	Khan et al., 2018	Epidemiological study	Adult population of a district	1700	39.4+13.9	ISI, door to door survey	Insomnia	9
13	Sreedharan et al., 2016	Cohort study	PSG proven OSA patients	152	53.81+12.01	PSG	Insomnia, EDS	7
14	Jaisoorya et al., 2018	Cross sectional study	General patients at OPD(PHCs)	7017	41.4+11.1	ISI	Insomnia	8
15	Panda et al., 2018	Observational study	Patients with definite and probable ALS	40	56.6+9.4	ESS, PSQI	RLS, Insomnia	6
16	Mondal et al., 2018	Observational cross sectional study	Psychiatric outpatients	500	42.2+15.3	ISI	Insomnia	7
17	Jain et al., 2014	Prospective study	Traumatic brain injury patients	204	33.34+12.9	ISI	Insomnia	6
19	Naik et al., 2021	Prospective observational study	Patients aged >18 years with laboratory- confirmed COVID-19	1234	41.6+14.2	Interviews conducted by trained residents	Insomnia	7
20	Tomar et al., 2018	Cross sectional	Post-traumatic brain injury patients	100	35.07+12.88	ISI, PHQ-9	Insomnia	9
21	A. Kumar et al., 2021	Cross-sectional study	Patients with chronic liver disease	131	48.7+12.31	PHQ-9, PSQI	RLS, Insomnia	8
22	Devaraj et al., 2013	Cross sectional	Patients with a recent Myocardial Infarction	44	57.5+10.44	PSG, ESS, BQ	OSA, Insomnia	8
23	Ramakrishnan et al., 2012	Descriptive study	General patients visited sleep centre	1765	All age patients	PSG	OSA, Insomnia	6
24	N. Kumar et al., 2021	Cross-sectional study	Parkinson’s disease	832	66.9+18.39	Online survey with validated questionnaire	RLS, Insomnia	6
25	Jasti et al., 2018	Cross-sectional study	Parkinsonism patients	168	65.3+12.8	PSQI, ESS, PDSS- 2	OSA, EDS, Insomnia	7
26	Kishan et al., 2021	Cross Sectional observational	Chronic heart failure patients	103	62.65+11.8	ESS, STOP-BANG, BQ	OSA	7
27	Shanmugam et al., 2015	Cross-sectional prospective observational study	CKD patients	302	All age patients	BQ	OSA	7
28	A. Singh et al., 2021	Cross sectional study	Type 2 diabetes patients	149	63.42+12.31	STOP-BANG	OSA	9
29	Viswanathan et al., 2017	Cross sectional study	Type 2 diabetes patients	203	54+8	AHI	OSA	6
30	Malik et al., 2017	Cross sectional study	Type 2 diabetes patients	62	60.82+11.34	PSG	OSA	8
31	Goyal et al., 2018	School-based cross- sectional	School students	1346	6.81+2.18	SRBD scale	OSA	9
32	S. K. Sharma & Sreenivas, 2010	Cross sectional study	Middle aged urban Indians in South Delhi	351	43+13.2	PSG	OSA	8
33	S. K. Sharma et al., 2010	Cross sectional study	Individuals of either gender aged 30-65 years	365	47.5+13.8	Validated questionnaire, PSG	OSA	7
34	Shailly Saxena, 2006	Observational cross sectional study	Individuals above 18 years of age	1188	44.27+10.79	Sleep questionnaires	OSA	7
35	Joseph et al., 2020	Cross sectional study	Pregnant women	214	27.2+4.7	STOP-BANG, ESS	OSA	5
36	Choudhury et al., 2019	Cross sectional study	Rural community of Odisha	200	50+16.3	BQ	OSA, EDS	6
37	Pinto et al., 2018	Observational cross sectional study	Adult population	321	39.43+15.6	ESS, Modified BQ	OSA	8
38	K. Aggarwal et al., 2021	Cross-sectional and observational study	Undergraduate college students	493	20.3+1.53	PSQI	OSA	7
39	Agrawal et al., 2011	Cross sectional study	Patients with and without OSA	272	45.29+8.96	PSG	OSA	8
40	Surya Kant, 2019	Prospective observational study	Patients of Pulmonology Outpatient Department	48	All age patients	PSG	OSA	6
41	Anand et al., 2021	Cross sectional prospective study	Children with Down syndrome	53	7.4+3.47	PSG	OSA	4
42	Nanaware et al., 2006	Retrospective study	Suspected sleep disordered breathing children under 18 years	56	11.5+5.13	PSG	OSA	4
43	Kaswan et al., 2021	Prospective cross section	Diabetes mellitus patient	362	55.7+10	STOP-BANG, ESS	OSA	9
44	Devaraj et al., 2017	Prospective cohort	Patients underwent non-cardiac surgery	182	48.9+14.41	PSG, STOP-BANG	OSA	9
45	Lorenzoni et al., 2019	Observational cross sectional study	Obese children	45	10.5+0.75	PSG	OSA	6
46	Dixit et al., 2018	Cross sectional study	Adult patients of bronchial asthma	50	48.16+14.9	PSG	OSA	6
47	Tripathi et al., 2019	Cross sectional study	Elderly completely edentulous patients	183	62.5+1.97	PSG, ESS	OSA	9
48	Reddy et al., 2009	Cross sectional, community based study	Middle-aged urban of South Delhi	2505	47.5+13.8	PSG	OSA	9
49	S. K. Mahajan et al., 2021	Cross sectional study	Patients with acute coronary syndrome	66	57.7+11.1	PSG	OSA	8
50	Prasad et al., 2017	Comparative study	Subjects who underwent polysomnography at sleep lab	210	46.5+13.7	PSG	OSA	8
51	Kamgo et al., 2022	Prospective observational study	Interstitial Lung Disease patients	41	55.5 10	PSG	OSA	6
52	R. Kumar et al., 2013	Cross Sectional observational	Patients with asthma and COPD	400	35.8 7.9	ESS, BQ	OSA	8
53	Sehgal et al., 2016	Cross sectional study	Patients with metabolic syndrome	50	47.1 6.6	PSG, ESS	OSA	6
54	Nair et al., 2022	Cross sectional study	Patients with sleep disordered breathing	142	49.7 14.6	Level 1 PSG	OSA	10
55	Priyadarshini et al., 2017	Observational cross sectional study	Obese patients seeking bariatric surgery	27	42.4 10.5	PSG, ESS, BQ	OSA, EDS	7
56	Nattusami et al., 2021	Cross sectional study	Patients with stable COPD	301	59.6 10	PSG, ESS	OSA, EDS	10
57	Shoib et al., 2017	Cross-sectional study	Patients suffering from depression	182	54.89 12.93	PSG	OSA	10
58	Utpat et al., 2020	Prospective observational study	Interstitial lung disease patients	100	56.44 20.52	PSG	OSA	9
59	Bhaisare et al., 2022	Prospective observational study	Diagnosed lung cancer patients	30	55 8	PSG, ESS	OSA	8
60	Agrawal et al., 2013	Cross sectional study	Patients of ASA I-III scheduled for elective surgical procedures under anesthesia	204	42.7 15.08	STOP-BANG	OSA	7
61	Kaul et al., 2001	Cross Sectional observational study	Primary sleep disturbances patients	60	46.36 7.89	PSG	OSA	7
62	Jain & Sahni, 2002	Prospective observational study	Children adenoidectomy and/or tonsillectomy	40	8 3.15	PSG	OSA	6
63	Ghosh et al., 2020	Cross sectional study	Population study	1000	47 13	BQ	OSA, EDS	7
64	Tripathi et al., 2018	Cross Sectional observational study	Non-obese male subjects	120	45 7.8	PSG	OSA	5
65	P. Singh et al., 2022	Prospective study	Coronary artery disease patients	100	35.14 4.35	PSG	OSA	7
66	Dubey et al., 2018	Cross sectional study	Male Driving License recipients	542	31.8 13.2	STOP-BANG	OSA	9
67	Mathiyalagen et al., 2019	Cross sectional study	Patients attending a non-communicable disease clinic	473	51 11.34	Pre-tested semi- structured questionnaire	OSA	10
68	M. Kumar et al., 2021	prospective cross- sectional study	Patients with cirrhosis	1098	48.3 10.5	PSQI, ESS	OSA, EDS	10
69	Rohatgi et al., 2018	Preliminary study	Patients suffering from schizophrenia spectrum disorder	43	32.2 10.1	Berlin Questionnaire	OSA	8
70	L. Ahmad et al., 2020	Prospective, cross- sectional hospital- based study	Adolescent patients who reported to Orthodontic OPD	213	16 3.4	STOP-BANG	OSA	9
71	Selvaraj & Keshavamurthy, 2016	Cross sectional study	Parkinson’s Disease patients	50	57.16 6.6	PDSS, ESS	OSA	6
72	Bhagawati et al., 2019	Cross-sectional study	Patients with CKD who were >18 years of age	300	47.58 15.04	IRLSSG rating scale	RLS	10
73	Pinheiro et al., 2020	Cross sectional study	Type-2 diabetes	210	56 13.5	IRLSSG rating scale	RLS	6
74	R. Gupta et al., 2017	Population based door to door study	Subjects 18 and 84 years in Himalayan and Sub-Himalayan region	1689	35.2 10.9	Cambridge-Hopkins RLS diagnostic questionnaire	RLS	9
75	Rangarajan et al., 2007	Cross-sectional, questionnaire-based study	Adult residents of Bangalore	1266	49.4 24.4	Face-to-face interview, IRLSSG scale	RLS	7
76	Bellur et al., 2022	Cross-sectional observational study	College students	4211	18 1.48	PSQI, ESS	RLS	7
77	Joseph et al., 2022	Cross-sectional study	General population of Mangalore	202	29 13	PSQI	RLS	6
78	R. Gupta et al., 2012	Cross sectional study	Patients who presented with insomnia or leg pain	653	39.86 12.8	IRLS Hindi version	RLS	7
79	Halkurike- Jayadevappa et al., 2019	Prospective observational study	Adult patients with cirrhosis	356	48 25.6	IRLS scoring system	RLS	9
80	Bhowmik et al., 2003	Comperative study	Hemodialysis patients	121	34.5 11.1	Predesigned questionnaire	RLS	5
81	R. Gupta et al., 2018	Cross sectional observational study	Patients with opioid use disorder	19	30.2 10.4	Predesigned	RLS	6
82	Bathla et al., 2016	Cross sectional study	Patients undergoing hemodialysis	194	54.5+15	Face-to-face interview, IRLS questionnaire	RLS	7
83	A. Gupta et al., 2017	Prospective study	Stroke patients	346	54.87+12.03	Pre-structured sleep questionnaire	RLS	9
84	Velu et al., 2022	Cross sectional study	Patients with End-stage kidney disease	148	44+14.5	ESS, PSQI	RLS, EDS	10
85	R. Gupta et al., 2013	Cross sectional observational study	Subjects presenting to psychiatry OPD with complaints of depressive illness	54	35.58+33.22	MINI-Plus Interview, IRLSSG criteria	RLS	9
86	Raj & Ramesh, 2021	Cross sectional study	Patients diagnosed with Tuberculosis	206	41+16.2	PSQI, ESS	RLS, EDS	6
87	Raj et al., 2019	Cross-sectional study	Type 2 diabetes patients	102	56.88+10.98	ESS	RLS, EDS	7
88	Kaur & Singh, 2017	Cross-sectional study	College students	1215	19.5+4.7	ESS	EDS	4
89	A. Singh et al., 2017	Prospective cross sectional study	Subjects with age groups ≥ 25 years	1512	42.6+11.2	ESS, face to face interview	EDS	5
90	Roopa et al., 2010	Cross sectional study	Random subjects aged 20-76 from Chennai Urban Rural	358	43.7+12.7	Standard validated questionnaire	EDS	8
91	Krishnaswamy et al., 2016	Prospective study	Bus drivers working in Karnataka State Road Transportation Corporation	180	41.4+9.3	ESS	EDS	6
92	Ghante et al., 2021	Cross-sectional study	Postnatal women	225	25.16+3.98	ESS, PSQI	EDS	7
93	Dey et al., 2020	Cross-sectional study	Doctors from all the clinical department	100	35.32+6.21	PSQI, ESS	EDS	8
94	Venkatnarayan et al., 2022	Cross sectional observational study	OSA patients	100	49.5+13.3	PSG	EDS	5
95	Shoib et al., 2022	Cross-sectional study	OSA patients	182	54.89+12.89	PSG, ESS	EDS	6
96	Samanta et al., 2013	Cross sectional observational study	Patients of cirrhosis	100	49.1+11.4	PSQI, ESS	EDS	5
97	P. Sharma et al., 2016	Cross-sectional study	Patients with schizophrenia	100	30.63+8.7	PSQI, ESS	EDS	7
98	Sreedharan et al., 2021	Prospective study	Patients getting admitted for coronary artery bypass surgery	120	60+11.5	STOP-BANG	EDS	7
99	S. Mahajan et al., 2012	Cross sectional observational study	Patients on maintenance hemodialysis for >3 months	47	37.1+13.1	ESS	EDS	5
100	Kadam Y, Patil S, Waghachavare V, Gore A, 2016	Cross sectional study	College students from an urban area	900	19.3+1.5	Pre tested self- administered questionnaire	EDS	6

Source: Systematic Review of Prevalence of Sleep Problems in India: A Wake- up Call for Promotion of Sleep Health by Karuna Datta, Anna Bhutambare, Hruda Nanda Mallickfd

Note: CKD: Chronic Kidney Disease, OSA: Obstructive sleep apnea, RLS: Restless Legs Syndrome, EDS: Excessive daytime sleepiness PSQI: Pittsburgh Sleep Quality Index, PHC: Primary Health Centre, ESS: Epworth Sleepiness Scale, ISI: Insomnia Severity Index, PSG: Polysomnograpgy, PHQ-9: Patients Health Questionnaire, BDI: Beck Depression Inventory, BSA: Berlin Sleep Apnea, BQ: Berlin Questionnaire, PDSS-2: Parkinson Disease Sleep Score-2, AHI: Apnea Hypopnea Index, SRBD: Sleep Related Breathing Disorder, COPD: Chronic Obstructive Pulmonary Disease, PDSS-III: Parkinson Disease Sleep Score Part-III, IRLSSG: International Restless Legs Syndrome Study Group, IRLS: International Restless Legs Syndrome severity scoring, MINIPlus: Mini International Neuropsychiatric Interview Plus, JBI: Joanna Briggs Institute

2025 Healthcare and Life Sciences Investment Outlook

Mankind versus ChatGPT: Our Caveat for 2025

For the first time in AI’s and mankind’s history, the line between what is human and what is AI-driven technology is increasingly blurring, we are witnessing that ChatGPT and other OpenAI models, can influence the rates of false negatives and false positives in various healthcare and investment applications including algorithms that make investment calls based on future predictions. We have been making annual healthcare and life sciences investment predictions since 2013 with 95% accuracy except during the Covid pandemic years. It seems that ChatGPT itself is turning out to be a black swan event for the algorithms which are predicting the future so accurately in the past. As ChatGPT becomes mainstream, we need to understand the “Confusion Matrix” (see chart below) that will ensure with the power of AI and ChatGPT versus the humans in the future as more and more AI-generated content and analytics proliferates the world in 2025 and beyond.

Confusion Matrix for AI ChatGPT and Human Predictions

As industries including, Healthcare and Lifesciences is adopting AI very rapidly for delivering healthcare and so do the Banking and Financial Services, investment managers using AI-driven algos for investment calls. We would need to take cognizant of the False Negatives and False Positive that would elevate the risks and mitigate accordingly. We have included AI as one of the factors in our 2025 Outlook, India Healthcare and Lifesciences Investment Heatmap.

2025: Heal the World – From Geo Politics to Socio Politics

In our 2024 forecast last year we included Geopolitics for the first time in our investment heatmap as the signals were emerging as early as mid-2023. While 2024 witnessed global geopolitics upheaval with regime changes through democratic elections and other means with over 60 wars and armed conflicts ongoing around the world, we were seeing signals of slowdown in growth and investments in Q12024 itself. As a result, as we exited 2024, the growth and investment climate slowed down significantly.

The broad global theme for 2025 is “Heal the World” for better outlook for 2026 and beyond. If we are able to heal the world with robust socio political agenda it would turn out to be the future prosperity of mankind.

2025: India’s Healthcare and Lifesciences Innovation and Business Models

India was also not insulated with the global geopolitics impact. In 2024, there was ~50% decline in capex and investments in the sector. We expect 2025 to continue to be a weak year for investments in the sector. After our general elections, there were uncertainties in our region and further slowing of investment and capex cycles on the back of global slowdown. Healthcare is a big creator of employment and it should not slow down any further in 2025.

Since Q12024, the signals were towards robust investments in early stage innovations and growth in new age business models which we have been labelling as “cross-domain” investment ideas. In March 2024, we released 2024 – India Healthcare And Life Sciences Investment Manifesto | Kapil Khandelwal KK covering key 40 bets that will be an opportunity to invest in the sector that will witness an upside beyond the market returns for the sector over the next 5 years. This will accelerate the investments that was with USD 857 million in 2024 to reach a unicorn status of over USD 1 billion in 2025. Fortunately, this is the only segment witnessing positive growth in investments in 2024 and continues to attract robust growth and investments.

Hence, we have made attempts to analyse International ‘Geo Politics’ as a separate factor and bolt-on-top of our algo predictive models to adjust our heat map for 2024 to accurately predict whether the heat is on in our 2025 Investment Heat Map.

The wave of optimism for 2025 in Indian healthcare and life sciences stems from the following:

Over half of Indian consumers are increasingly curious to understand their body and well-being by ‘listening to their body’. Innovators and start ups are exploring this opportunity to scale up their ventures.
Many of the start-ups of the Pre Covid India Stack in healthcare are either pivoting to including AI tech or will perish as AI goes turbo. We are expecting around 450 such start ups at this stage of AI upgrade.
Agentic AI effectively turbocharges the Do It For Me (DIFM) healthcare economy. Early adopters include GenZ and Millennials (approx 50% of Indians) users who will have their own bots or AI agents helping them choose products and execute transactions in adoption of healthcare products and services as the line between what is human and what is technology will be blurring. Competition will tick-up as starts-ups grow.
“AI for All is not All” as consumers are getting more consumerised for their health needs. AI cannot solve it all for all of Indian consumers healthcare needs. These include Gen X and Seniors (approx 44% of Indians) are skeptics and late adopters. This innovative products to serve these cohorts is key.
New business models/incubation for investments are emerging (see our 40 Future Bets in Healthcare 2024 – India Healthcare And Life Sciences Investment Manifesto | Kapil Khandelwal KK) that are cross-domain and will be a potential USD 50 billion addition to India’s GPD in next 5 years.
Healthcare real estate will also explore cross-domain concepts to fit consumer needs.
Wellness is now an ‘Avatar’ that is experiential and connects with other lifestyle domains such as beauty, cosmetics, travel, tourism, hospitality, food, technology, wearables tech, work environment and many more. Holistic innovation in experiential longevity is emerging.
Alternative therapies are now body rejuvenation biohacks that traditional and alternative medicine and wellness cannot provide or fulfill completely and which health fascism fuels. Indian GenZ and Millennials are leading this change.
New age innovative medical integrative DIFM models will be a push for medical and wellness tourism repositioning for India medical tourism.
In 2024, the BSE Healthcare Index was one of the standout performers, delivering an impressive 40% year-to-date (YTD) return. This trend continues in 2025.
The valuations have come back to realistic levels to peak by 2026-27.
Private hospitals are now aggressively embarking on increasing bed capacity after a phase of consolidation in 2024.
M&A and buyouts are expected to continue to be buoyant.
Healthcare real estate are expected to launch and kick off innovative cross-domain formats.

The 2025 India Healthcare and Life Sciences Investment Heat Map is as under:

Healthcare Financing

With mental health needs and healthcare fascism at its peak, newer products and services for financing longevity and healthy lifestyle for the Gen Alpha and Gen Z are emerging. Cross domain models of business are emerging to address the needs to finance consumers needs to such emerging products and services.

2025 Outlook: Moderate

What may go wrong: false claims by online influencers, right pricing, reach and penetration to consumers, improper lifestyle based consumer segmentation, business volatility in some NBFCs, newer regulations on consumer credits by RBI, lower consumer spending and financing, outstanding credit cards debt
What’s going right: AI intervention and solutions, lower interest rates,

Medical Education

Medical education content is no longer the marker for better valuation and funding. The market has flipped to buyers’ market. The investors are no longer entering into opportunities at the current valuations and will lead to rerating downwards. Need major reforms in the medical education sector.

2025 Outlook: Low

What may go wrong: lower student enrollment, regulatory issues, new emerging careers in industry, accreditation and learning models, international players and competition
What’s going right: AI-generated content creation, immersive content, stable valuations

Med Tech Innovation and Life Sciences Discovery and Clinical Development

Trump Administration and the US BioSecure Act will be a positive. India has to enter the big league of biologics with global partnerships as Chinese firms will face headwinds. Cross domain innovation with AI is the key to leapfrog in the global race. Also India needs to reinforce its success in Covid vaccine development to reignite confidence in India. Expect a major IPO.

2025 Outlook: Moderate

What may go wrong: over dependence on Chinese players, slower reverse brain drain transition of drug hunters from US, low qualified life sciences professionals pool, lower grant funding, no further sops in the 2025 finance budget
What may go right: emerging social innovation models, market appropriate solution development, native AI models

Pharma and Therapeutic Solutions

Volume growth in the domestic markets, US generics price erosion, with the softening of input costs, ongoing decoupling of supply chain with China and currency depreciation to continue in 2025, will improve the margins very marginally. The companies with strong cash positions will increase capex and also buyouts and M&A activity. Not any major name IPOs expected.

2025 Outlook: Moderate

What may go wrong: Slower China decoupling of supply chain, continuing US generics markets prices decline, potential increase in tariffs by the US under Trump regime, increased APIs prices, continuing domestic market volume degrowth, no further sops in the 2025 finance budget
What may go right: US BioSecure Act to favour India, increased R&D spend, new products pipeline, newer capex cycles, multi-year high in US active drug shortages

Healthcare Providers

Capacity creation will now be around 2500 beds in tier 2 and 3 cities. Funding cycles improve as internal accurals improve for fresh capex and capacity expansions and inorganic expansions. Expect a few IPOs, buyouts and exits via secondary sale.

2025 Outlook: Hot

What may go wrong: margin pressures, supply and demand mismatch in micromarkets, lower medical tourists arrivals, rising valuations, stable margins
What may go right: asset-lite models, launching into new medical tourism markets

Healthcare Insurance

Payors are seeing insurance penetration grow since the Covid pandemic. Newer markets in the GenZ and Millennials cohorts and geographically tier-2 and 3 cities are the essential for growth. Bundled products and services for health and wellbeing is the key. AI modelling will assist in accurate underwriting of risks. Agentic AI entry to change the solicitation and selling customised bundled products.

2025 Outlook: Hot

What may go wrong: bundled product for consumer needs, product approvals, risk mitigation for new products, consumers need for longevity, agentic AI to connect consumers, payors and providers for seamless services
What may go right: Consumer demand, reduced loss ratios, AI fraud detecting agents

Health Retail

Anti-digital trend is catching up with consumers expecting analogic human to human touch for consuming healthcare products and services in cross-domain settings which is now perceived aspirational and desirable. Many digital business models need to tweak their phydigital presence mix. Its back to innovative traditional health retail settings.

2025 Outlook: Hot

What may go wrong: failing to provide the human to human touch points, talent for new age health retail settings, anti-digital pivoting, wrong business model assumptions
What may go right: exits in failed business models, profitability focus, phydigital presence

Wellness

The past wellness definition is no longer relevant. New age ‘Gen-Z’ed wellness business models and innovation is emerging which brings in the cross-domain experiential products and services. Redefinition of wellness is the key and will show case the future winners. These innovations will fuel India’s new age wellness tourism too.

2024 Outlook: Hot

What may go wrong: regulation, talent and skills in cross domain products and services, micro market segmentation, faster beta testing, new mass market business models, spurious social media channels, fake outcome/claims
What may go right: Gen Z micro segmentation, wearables, biosensors, newer phydigital formats

Alternative Therapies

Redefined by cross-domain influences, emerging tech, wearables, biosensors, cutting-edge innovation in life sciences with other domains fueled by GenZ experimentation with new biohacking and health fascism expressions. It is going to be the next destination of value care in healthcare emerging from real need and experience of consumers for Do It For Me (DIFM) healthcare.

2025 Outlook: Hot

What’s going wrong: regulations, consumer education and confidence, clinical research, new product development, new mass market business models, repeat sales, spurious social media channels, fake outcome/claims, wrong Gen Z role models, developing phydigital formats
What may go right: discretionary consumer spending, newer cross-vertical innovative business models, mainstream complementary treatment, wearables, biosensors

Moving Forward

2025 will be a pivoting year for mankind, healthcare and investing as AI for All is not All.

Happy investing and stay strong!

Media Coverage

M&A, Buyouts in Healthcare to Remain Coverage in VC Circle

2025 India Healthcare and LifeSciences Investment Outlook Coverage in Express Pharma Feb 2025

Rebooting Age: Long-Living India

Rebooting Age : Long-living India

Podcast

QuoteUnQuote with KK and Dr. Deepak Kumar Saini, Convener, Longevity India and Professor, Dept. of Developmental Biology & Genetics Indian Institute of Science (IISC), discuss Bet #3 on anti-ageing tech and products that is going to be a major trend in the next 5 years. Why is it so?

As 50s is the new 30s now. Present Genx and seniors would like to reverse age or age slowly. By 2047, over 300 million Indian would be Senior Citizens and our dependency ratio will be around 40%. Indian would like to extend their lifespan 20% to 50%. But the trick here is to ensure that the end of life after prolonged life is a quick process rather than a prolonged decline.

Bharatvarsh – Pilgrim Nation: The Land of Spiritual Wellness Travel

Bharatvarsh: The Destinations for Spiritual Wellness Journeys

Podcast

QuoteUnquote with KK and Dr Devdutt Patnaik, India’s top mythologist and author discusses on our bet #our Bet #22 on mythological/pilgrimage wellness/health that is going to be a major trend in the next 5 years from our 2024 India healthcare and lifesciences investment manifesto. Devdutt, clears the issues on Bharatvarsh, sprituality, spiritualism, the Great Indian Pilgrimage, destinations across Hindu, Jain, Buddhist followers, ancient practices and modern beliefs. He also discusses various emerging counter trends around non-traditional spirituality, conspirituality amongst the extreme rightists and wokes, fake narrative emerging out of AI and ChatGPT and how belief systems are being altered around practice of spirituality and religion.

Excerpts

What is Spirituality?

How is Religion Different from Spirituality?

How is Bharatvarsh defined by Politicians, Pilgrims and Vedas?

Are there Counter Trends to Spiritualism?

How do we address the Saviour Mindset?

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Veda, Weed and Yoga: Is it ‘Xeno’ to XYZ Gen?

GWI-Wellness Real Estate-2024

Global Wellness Trends - Trends in Spiritual and Numinous Moments in Architecture

Will Ayodhya Be The Mecca Of Medical Tourism? | Kapil Khandelwal KK

Mooring Around the Future of Chips in AI-dominated India

Podcast

QuoteUnquote with KK and Nitin Dahad, Tech Evangelist, Editor embedded.com, Writer

Also Watch

Raghu Panicker, CEO of Kaynes Semicon, gives us some background to the origins of the current semiconductor industry in India from the 1980s by two key figures: M.J Zarabi and Wally Rhines.

Hitesh Garg, India country manager for NXP Semiconductors, talks about key markets for NXP globally and in India, particularly automotive and industrial.

Satya Gupta, a veteran of the Indian electronics industry in India. He has several influential roles in the industry and in policymaking

Bhanupriya Krishna, founder and managing director of Perceptives Solutions, talks about the lack of talent for addressing the semiconductor manufacturing industry in India

Pradeep Vajram challenges the current thinking in India to develop chips and IP for India only, highlighting that scale is key for investors in Indian semiconductor startups