Unveiling the Connection Between BMI & Social Media Data in Insurance

A primary concern among all insurers is how to adequately and accurately assess their clients’ various risk factors. In this pursuit, social media and insurance analytics can work together to give insurance brokers better insight into risk factors that change costs and outcomes. In turn, they can effectively:

• Structure their product offerings
• Offer better premium pricing for profitability reasons
• Remain competitive and relevant in the market

The Intersection of Social Media and Insurance: Exploring the BMI Connection in Social Data

Unlike with property insurance, risk assessment in health insurance is severely inhibited by various regulations designed to protect individuals' privacy rights. But thanks to technological advancements and extensive research, novel solutions are emerging to solve this problem.

Read on to learn how body mass index is reflected in social data and how insurers can utilize this to refine their risk assessment strategies. 

Background

Despite a slight reduction in the growth rate of health-related government expenditure to 4.2 percent in 2021, from a record 9.7 percent high in 2020, estimates suggest the cost of healthcare is still on an upward trajectory, with the expectation that national health spending will peak at $6.8 billion by 2030. 

In the private health insurance sector, the situation is grim at best. As far back as 2018, a study determined a significant disparity between Medicare hospital prices and the amount paid by private insurance providers. Private insurers incurred an average of 247 percent more than Medicare in hospital prices. 

As a result, insurers are forced to raise rates on policies that cover medical expenses. While increasing premium pricing is effective in the short term, it can negatively impact an insurer's competitiveness and relevance in the market.

A recent study suggests the insurance industry is set for more growth in 2022 and beyond, and in response, more parties are getting drawn to have a piece of the pie. 

In short, raising policy prices is not an effective long-term solution to the current crisis. More effective risk assessment is crucial for insurers to remain relevant by correctly identifying different risk segments and pricing premiums more competitively.

Body Mass Index (BMI)—  A Vital Risk Assessment Tool in Health Insurance

Studies suggest numerous factors are at play in increasing healthcare costs. However, obesity, chronic health conditions, and generally unhealthy lifestyles feature prominently as some of the driving causes of the healthcare cost crisis. 

To put it into perspective, a mere five percent of individuals with chronic conditions account for nearly half the cost incurred by insurers in hospital claim payments.

Obesity increases the risk of developing several serious health conditions, including heart disease, stroke, and diabetes. In addition, obesity can lead to chronic diseases such as arthritis; this, in turn, will require more treatment and subsequently increase the claim amounts incurred by insurers. 

Obesity is a worsening problem in the United States. According to the Centers for Disease Control and Prevention, the age-adjusted prevalence rate was 42.4 percent between 2017 and 2018. 

Given that unhealthy lifestyles contribute to obesity, which further exacerbates chronic conditions, it's proper to say that BMI is an underrated yet highly relevant metric in assessing an individual's health and the subsequent risks they pose to insurers. 

Social Media As an Ideal Alternative Data Source to Assess BMI

With the present regulations meant to protect consumer privacy, it's almost impossible to compel clients to self-report their BMI. 

Still, even if insurers could compel consumers to self-report their BMI, the values are highly likely to be skewed, as observed in several studies. Individuals may under- or overstate the figures to influence their policy premium prices in their favor or even for basic self-esteem issues.    

Social media, on the other hand, provides insurers (or any interested party) with unfiltered access to people's lives and their data.

Whether or not they're aware, individuals provide so much data about themselves each time they use social media. Seemingly mundane actions like posting a picture of a new car or liking an enticing food ad can gradually help social media and insurance companies develop the most comprehensive profile on an individual. 

But how is this relevant to developing a BMI profile?

A study demonstrated how social factors, in concert with other variables, contribute to many health conditions. In a few cases, social factors are the primary cause of obesity and, by extension, chronic health conditions.  

Social Data to Look Out for When Assessing BMI

Social media and insurance records have enormous amounts of data on individuals. However, the below factors are the most consequential for health. They are what insurers should focus on if they're to develop an accurate BMI score or risk assessment of their clients:

1. Demographic Profile

It's the most basic data that can be easily gleaned from social media and the most important. Obesity prevalence and BMI scores vary based on age, gender, and marital status.

Similarly, different people in different geographic locations are exposed to different diets that can affect their BMI scores positively or negatively. People are more likely to have higher BMI scores or be obese in places with a high density of food outlets/restaurants. 

2. Health Literacy

High levels of health literacy correlate to high obesity prevalence rates. This is because health-literate individuals know why they should adopt healthy lifestyles and how to go about it. Their commitment to look for and interact with health literacy content is also a good indicator of their health consciousness.

Insurers can analyze how frequently users engage with health literacy materials on social media. It can be that they occasionally read, share or like such content.  

3. Physical Activity

Regular or above-average physical activity is essential in keeping body fat content in check. Lack of regular physical activity is also known to correspond with higher BMI scores and could potentially contribute to obesity.

Posting pictures while cycling to work, in the gym, or physical recreation center can point toward a generally healthy lifestyle. Insurers can also train analytical social media and insurance models to parse their clients' social media profiles and determine their BMI.

4. Sleep Patterns

Inadequate sleep is known to tamper with hormones responsible for regulating satiation or hunger in the body. Without early intervention, lack of sleep can wreak havoc on individuals' perception of hunger, which may cause them to eat more or less.

Inefficiency in homeostatic function in the body can gradually develop into obesity and higher BMI scores. 

Social media usage analysis can shed light on an individual's sleep patterns. Additionally, users liking, tweeting, or sharing content related to insomnia or how to deal with it can point to irregular or unhealthy sleep patterns. 

5. Social Status

Insensitive as it might seem, individuals with higher social status are more likely to adopt healthier lifestyles and have lower BMI scores than those with low social status. 

For the most part, this phenomenon can be explained by Maslow's hierarchy of needs. High-status individuals have figured out their most basic physiological needs, i.e., food, and are keen on how they're perceived in society. This may lead to more healthy choices to fit with society's constructs.

Social media data on a person's level of education, income, and profession or occupation can be used to gauge their social status. 

Other equally important indicators of social status include:

• The number and quality of followers a user has
• How much engagement a user's posts receive (likes, shares, etc.)
• The location of the user's posts
• The type of content posted

Final Thoughts on the Future of Social Media and Insurance

Social data can provide immense and accurate insights into individuals' body mass index, an essential component in assessing their risk for insurance purposes. However, despite its usefulness, it can be nearly impossible for an organization to collect and analyze this enormous treasure trove of data by itself.

To learn more about how Pilotbird uses social data, request a demo. 

References About Social Media and Insurance

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(2022). Retrieved 13 July 2022, from https://www.pwc.com/us/en/industries/financial-services/library/next-in-insurance-top-issues.html

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CMS Office of the Actuary Releases 2021-2030 Projections of National Health Expenditures | CMS. (2022). Retrieved 13 July 2022, from https://www.cms.gov/newsroom/press-releases/cms-office-actuary-releases-2021-2030-projections-national-health-expenditures

Garon, T. (2022). Reliability of Self-Reported Data – Recall Bias — Financial Access Initiative. Retrieved 13 July 2022, from https://www.financialaccess.org/blog/2015/7/30/reliability-of-self-reported-data-recall-bias

Nations, U. (2022). LIFESTYLE DISEASES: An Economic Burden on the Health Services | United Nations. Retrieved 13 July 2022, from https://www.un.org/en/chronicle/article/lifestyle-diseases-economic-burden-health-services

Private Health Plans in the U.S. Pay Hospitals 247% of What Medicare Would Pay. (2022). Retrieved 13 July 2022, from https://www.rand.org/news/press/2020/09/18.html

Steyn, K., & Damasceno, A. (2022). Lifestyle and Related Risk Factors for Chronic Diseases. Retrieved 13 July 2022, from https://www.ncbi.nlm.nih.gov/books/NBK2290/