Tag: Chronic Kidney Disease

Chronic Kidney Disease

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.

Indians Sleeping Statistics in a (S)nap
Indians Sleeping Statistics in a (S)nap

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)
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

A Very Heavy and Weighty 2025 New Year Resolution!

A Very Heavy and Weighty 2025 New Year Resolution!

2025 New Year Resolutions

It’s that time of the year when we make New Year’s Resolutions. This year’s number one resolution that tops the chart is healthy diet and weight loss which is being wished by 51% of the people. Next is wishing for wealth which is wished by 21%. Finally comes spending quality time with friends and family which is wished by 14%. This is much lower this year post covid lockdown. Is there any correlation to the obesity trends in India with the New Year’s Resolutions for 2025?

Obesity Trends in India

Body Mass Index (BMI) scale is used to indicate if one is obese or not. The different classifications are as unde for India. Please note that this is not the same for other countries which may vary or are higher:

  • Normal BMI: 18.0-22.9 kg/m²
  • Overweight: 23.0-24.9 kg/m²
  • Obesity: ≥25 kg/m²

The prevalence of obesity has been increasing, with nearly one in four Indians now considered overweight. Approximately 24% of women and 23% of men aged 15-49 are classified as overweight or obese in India. Obesity rates are higher in urban areas (30% of men and 33% of women) compared to rural areas (19% of men and 25% of women).

Dietary Trends in India

The Economic Survey 2023-24 noted unhealthy diets and rising rates of obesity need to be tackled urgently to improve health parameters, in order to reap the gains of the country’s demographic dividend. Citing the Indian Council of Medical Research’s (ICMR) latest dietary guidelines, published in April this year, it notes the fact that 56.4% of the total disease burden in India is due to unhealthy diets. The ICMR report observes that the upsurge in the consumption of highly processed foods, laden with sugars and fat, coupled with reduced physical activity and limited access to diverse foods, exacerbate micronutrient deficiencies and overweight/obesity problems.

Correlating Obesity, Diet and 2025 New Year’s Resolutions

There seems to be a positive correlation between the weight loss and what people wishing to achieve in 2025 with respect to their diet and weight. These are many reasons for this correlation. These could be:

  • Calling for ill-Health: Obesity leads to chronic inflammation and impact longevity (listen to podcast on longevity https://open.spotify.com/episode/19pvPEE7f5UGgzJyXSlLsS?si=5f06687dfcf64232). Over the years, the body’s organs don’t function as effectively as they should. Damage to the pancreas, for example, leads to diabetes; damage to the heart leads to cardiovascular disease; and damage to the brain leads to dementia. And even if someone loses weight, the damage is not irreversible. (The liver is the only organ that can regenerate itself.) Obesity is also linked to many cancers, musculoskeletal problems, depression and obstructive sleep apnea. Some of the co-morbidities with obesity and overweight people include:
    • Chronic Kidney Disease
    • Type 2 Diabetes         
    • Cardiovascular Disease
    • PAD (Peripheral Arterial Disease)
    • Alzheimer’s  
    • Heart Failure
    • MASH (Fatty Liver Disease)

Sounds very alarming for increasing healthcare costs!

  • Better Employability: As per the National Health and Family Surveys, obese and over weight people have issues with their employability and their ability to work. This is tied to their overall health and their physical abilities. Hence being fit and normal BMI works in their favour.
  • Lifestyle, Fashion and Aesthetics: One of the most fundamental drivers of behavior is the desire to look attractive. Sales for personal care and beauty products easily exceed USD 25 billion by 2029, and sales for apparel reach USD 550 billion by 2029. This is a very aspiration segment. (listen to podcast: https://open.spotify.com/episode/36TCAlD1gglGXoWJtDa27o?si=09dd617d77434985). A significant number of Indians are unhappy with their weight and body image. A study involving participants from 65 countries found that Indians have lower body image satisfaction compared to many other nations.

Meeting and Beating the 2025 New Year Resolutions

Like any resolution, the compliance to any New Year Resolution is very low. Coming to managing ones weight reduction, the compliance is even lower. The level of compliance with weight loss programs among Indians varies widely. Several factors influence this, including cultural attitudes towards weight, accessibility to resources, and individual motivation.

  • Cultural Attitudes: In many parts of India, there is a cultural acceptance of larger body sizes, which can affect motivation to lose weight.
  • Accessibility to Resources: Access to weight loss programs, gyms, and healthy food options can be limited, especially in rural areas.
  • Individual Motivation: Personal commitment and motivation play a crucial role. Many individuals start weight loss programs but struggle to maintain long-term adherence due to lifestyle challenges and lack of support.

With such low levels of compliance and issues surrounding it, what has the healthcare industry done to find solutions to the weighty problems?

Healthcare Industry’s Invasive and Non Invasive Solutions to Obesity

There are several invasive and non-invasive solutions to obesity reduction. Here’s a brief overview of both:

Invasive Solutions

  • Gastric Bypass Surgery: This procedure involves creating a small pouch from the stomach and connecting it directly to the small intestine. This bypasses a large part of the stomach and some of the small intestine, reducing the amount of food you can eat and absorb.
  • Gastric Sleeve Surgery: Also known as sleeve gastrectomy, this surgery removes a large portion of the stomach, leaving a tube-like structure. This limits the amount of food you can consume.
  • Adjustable Gastric Banding: A band is placed around the upper part of the stomach to create a small pouch that holds food. The band can be adjusted to control the amount of food intake.
  • Biliopancreatic Diversion with Duodenal Switch (BPD/DS): This complex surgery involves removing a portion of the stomach and bypassing a significant part of the small intestine. It reduces the amount of food intake and nutrient absorption

Invasive surgery is expensive and not affordable by many. Also, this has to be followed up with non-invasive and other cosmetic surgery later on.

Non-Invasive Solutions

  • CoolSculpting: This technique uses controlled cooling to freeze and destroy fat cells. The body then naturally eliminates these dead cells over time.
  • SculpSure: A laser-based treatment that targets and heats fat cells, causing them to break down and be absorbed by the body.
  • Kybella: An injectable treatment that destroys fat cells under the chin, improving the appearance of a double chin
  • Emsculpt: This procedure uses high-intensity focused electromagnetic energy to induce muscle contractions, which can help reduce fat and build muscle.
  • Lifestyle Modifications: Diet and exercise remain fundamental. Behavioral therapy and support groups can also be effective in managing obesity

Each method has its own benefits and risks, and the best choice depends on individual health conditions, preferences, and goals.

GLP-1 The Magic Pill for Obesity

During 2024, a hype has been created over social media, celebrities both in Bollywood and Hollywood about GLP-1 (glucagon-like peptide-1), the wonder drug and magic pill for weight reduction. For the scientifically advanced beings, brief overview of the mechanism of action of GLP-1 (Glucagon-Like Peptide-1):

  • Secretion: GLP-1 is secreted by the intestinal L-cells in response to food intake.
  • Receptor Binding: GLP-1 binds to its receptors located in various organs, including the pancreas, brain, stomach, and heart.
  • Insulin Secretion: In the pancreas, GLP-1 enhances glucose-dependent insulin secretion.
  • Glucagon Suppression: It suppresses glucagon release, which helps lower blood glucose levels.
  • Gastric Emptying: GLP-1 slows gastric emptying, promoting satiety and reducing food intake.
  • Neuroprotection: It has neuroprotective effects and may improve cognitive function.

For the least scientifically advanced beings, GLP-1 works in reducing the food appetite and the weight of a person by 15-20%. In addition, GLP-1 also works on other co-morbidies such as

  • Diabetes Management: GLP-1 agonists are medications that help lower blood sugar levels by increasing insulin secretion and decreasing glucagon release. They also slow down gastric emptying, which helps control blood sugar spikes after meals.
  • Weight Loss: These medications are also effective for weight loss. They work by reducing appetite and increasing feelings of fullness, which can lead to reduced calorie intake and weight loss.
  • Cardiovascular Benefits: Some GLP-1 agonists have been shown to provide cardiovascular benefits, such as reducing the risk of heart attack and stroke in people with type 2 diabetes.
  • Potential Kidney Benefits: Emerging research suggests that GLP-1 agonists may also have protective effects on kidney function.
  • Parkinson, Alzheimer’s and Dementia: Early clinical research is showing effective results in patients with neuro issues with a lower risk of the cognitive issues (such as memory loss) that are often an early sign of dementia.
  • Addiction Management: This is still very early and GLP-1 is being tested on animals and showing positive results on addiction to alcohol and nicotine.

Statutory Warning:

All drugs have side effects, and the GLP-1s are no exception. The most common ones are gastro-intestinal problems, for example diarrhea. In addition, the drugs cause the loss of lean muscle mass, which is particularly concerning for the elderly. Moreover, newer formulations or the next generation of GLP-1 are also being researched and will circumvent the side effects.

GLP-1 in India

In India, several GLP-1 (glucagon-like peptide-1) receptor agonists are available for the management of diabetes and obesity. Here are some of the notable ones:

  • Liraglutide: Marketed under the brand name Lirafit™ by Glenmark Pharmaceuticals, this drug is used to improve glycemic control in adults with type 2 diabetes.
  • Semaglutide: Available as an oral formulation, this drug is marketed by Novo Nordisk India and is used for diabetes management.
  • Exenatide: Another GLP-1 agonist used for diabetes treatment, though specific brand names in India may vary.

I am also informed that there is a venture working on GLP-1 extracted from plants peptides under development.

As for me, I am wishing that 2025 will bring in more innovation in GLP-1 solutions which are more effective!

Happy New Year 2025!