literature review of insurance

• DOI: 10.18488/journal.1.2018.81.28.33
• Corpus ID: 148617321

Insurance Awareness: A Literature Review

• N. Ismail , M. Husin , +1 author Normaisarah Binti Abdul Manaf
• Published 2018
• Business, Economics
• International journal of Asian social science

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Mapping in the topic of mathematical model in paddy agricultural insurance based on bibliometric analysis: a systematic review approach, impact of government health and education expenditures on insurance demand: ardl model, świadomość ubezpieczeniowa pracowników biur rachunkowych w polsce, 29 references, awareness and willingness to pay for health insurance: a study of darjeeling district, awareness and impact of globalization of life insurance in india.

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An Empirical Study of the Level of Awareness towards Various Rights and Duties among the Insured Households in Rajasthan, India

Influence of awareness on the usage of motor third party insurance: a case study of kampala district., rural households’ awareness and willingness to pay for national health insurance scheme (nhis) in ilesha west local government area, osun state nigeria: a recursive bivariate probit approach, awareness and using status on long-term care insurance and insurance benefits, assessment of the level of awareness and perception of motor third party insurance in kampala, uganda, awareness of maternal health services among micro health insurance beneficiaries, insurance a ray of hope: a study on the level of awareness of private players in the insurance industry, [factors influencing oral insurance among children in chengdu]., related papers.

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New Perspectives on Insurance

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Ralph S J Koijen, Motohiro Yogo, New Perspectives on Insurance, The Review of Financial Studies , Volume 35, Issue 12, December 2022, Pages 5275–5286, https://doi.org/10.1093/rfs/hhac063

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This special issue originates from a dual submission conference with the NBER Insurance Working Group and the Corporate Finance Program in 2020. It brings a broader perspective on important frictions in insurance markets, including trust between insurers and policyholders, conflicts of interest among brokers, suboptimal policyholder behavior, and risk-based capital regulation. Several developments in the economy and the academic literature have provided an impetus for new perspectives, including the growth of savings products with minimum return guarantees, the global financial crisis, and intermediary asset pricing. We conclude with an overview of research questions that are promising for further exploration.

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Literature Review: Previous Literature for Understanding Life Insurance and Behavioral Demand for Life Insurance

• First Online: 28 December 2019

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• Wookjae Heo 2  

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In this chapter, a literature review focuses on behavioral demand for life insurance. Basic explanations about risk and risk management are discussed first to explain life insurance, specifically in the realm of personal finance. After understanding the general terminology about risk and risk management, the personal needs of life insurance buyers will be explained in this chapter. All explanations include a review of studies and scholarly works related to the research proposed for this analysis.

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Heo, W. (2020). Literature Review: Previous Literature for Understanding Life Insurance and Behavioral Demand for Life Insurance. In: The Demand for Life Insurance. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-36903-3_3

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Consumers' Insurance Literacy: Literature Review, Conceptual Definition, and Approach for a Measurement Instrument

2019, European Journal of Business and Management

Improved financial literacy is the key to informed decisions, protected consumers, financial independence, and peace of mind. Foremost literature reveals that while financial literacy required more special education to improve insurance literacy, the literature of consumers' insurance literacy is quite low. Defining and appropriately measuring insurance literacy is essential to understand the educational impact as well as barriers to better utilization of insurance products. Thus, we conducted a systematic literature review using PRISMA guidelines and analyzed 37 studies focusing on the construct validation criteria. This study developed a conceptual definition with an approach for a measurement instrument to address the current limitations in establishing a standardized measure of consumers' insurance literacy. We identified six knowledge dimensions and skill dimensions to be incorporated into an instrument developed to measure the insurance literacy construct. The study contributes to both insurance and financial literacy, and provide a foundation for further research into consumers' insurance literacy.

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How We Research Life Insurance Companies

Life insurance evaluation categories, data collection and scoring, financial stability, application process and online service features, policy types, policy features and riders, customer satisfaction, articles that use our methodology.

• Meet the Life Insurance Research & Reviews Team

We independently evaluate all of our recommendations. If you click on links we provide, we may receive compensation.

• Life Insurance
• Best Companies

How We Review and Rate Life Insurance Companies

Investopedia / Mira Norian

Investopedia’s list of the best life insurance companies is based on exhaustive research of 45 companies that sell life insurance policies. We reviewed each company’s financial strength, customer complaint record, digital application and policy management tools, policy offerings, and much more. This guide explains how we determined these categories and criteria, the methods we used to score each company, and how we ultimately chose the best life insurance companies.

Our editors and researchers independently evaluate all recommended products and services. If you click on the links we provide, we may receive compensation. Our advertising partnerships are not a factor in evaluating products, though they may affect the order of products you see listed in our articles.

We combined subject matter expertise, consumer survey and company survey data, and industry research to create a quantitative model that scores each company based on six major categories and 70 criteria.

In March 2024, we surveyed 500 people who had gotten a whole, term, or universal life insurance policy in the prior 24 months. We used the results to inform our criteria, weighting, and scoring process for our 2024 best life insurance companies rubric. We adjusted the weights for policy types and features, application processes, and online tools based on the survey results. We learned that life insurance buyers most value financial strength and costs, as well as the ability to buy the specific coverage amount they want. Top motivations are covering burial costs and replacing income. 

We determined that 45 life insurance companies met our minimum standard for financial strength, customer satisfaction, and online transparency. We gathered 70 evaluation criteria for each company, resulting in 3,150 data points. Data was collected between May 20 and July 3, 2024, and sourced from company webpages, media representatives, third-party rating agencies (AM Best, NAIC, and J.D. Power), and customer service calls.

Based on a combination of subject matter expertise, the results of our consumer survey, and third-party consumer research from the insurance trade association LIMRA, we developed the following category weights.

These categories included 70 criteria. We weighted 30 but collected the other 40 for editorial reasons and for use in future reviews. 

Through our data collection and review process, Investopedia has provided you with an unbiased and thorough review of the top life insurance companies.

• Data points are scored on a 0.00 - 1.00 scale
• Binary criteria = [0,1]
• Scaled criteria (e.g., 5-point) = [0.00, 0.25, 0.50, 0.75, 1.00]
• Continuous criteria: If higher values indicate better results (e.g., maximum death benefit), the lowest value in the database was re-scaled to a score of 0.00, and the highest was re-scaled to 1.00. If lower values indicate better results (e.g., premiums), the highest value received a score of 0.00, and the lowest a score of 1.00. All other values received scores relative to their distance from the extremes.  

Consumers need to trust that the life insurance company they choose will be stable enough to last as long as their life insurance policy is in force, which could be decades. Companies must also have the financial strength to fulfill their obligations to pay claims, which could amount to millions of dollars for a single policyholder.

Our survey results showed that financial stability was a crucial consideration for insurance consumers. We considered only the 45 companies that fared the best in a key measure of financial stability to ensure we only recommend companies that can pay their claims for years to come.

To assess each company's financial stability, we considered its AM Best rating. AM Best was founded in 1899 as the world’s first credit rating agency. Today, it is the largest credit rating agency in the world specializing in the insurance industry. It conducts independent assessments of the creditworthiness of more than 16,000 insurance companies, judging their ability to pay claims, debts, and other financial obligations.  

AM Best rates insurance companies on a scale from A++ to D-. We only included companies in our rubric with at least an A- or “Excellent” financial strength rating, meaning AM Best believes they have “an excellent ability to meet their ongoing insurance obligations.”

We scored AM Best ratings on a scale from 0.7692 - 1, in steps of 0.077, where an A- rating received the lowest score on our scale, and an A++ received the highest.

Year Established

For editorial reasons, we collected data on when each insurance company was established. While we didn’t score this data, we thought it provided some insight on each company’s financial stability.

State Availability

We also looked at where each life insurance company is licensed to sell policies. We didn’t score this data, but we only considered companies that at least operate throughout the continental United States.

While it’s important to have conversations with licensed agents as part of the buying process, consumers should also be able to buy and manage policies digitally, just like they can with other financial products.

To evaluate the application process and online tools, we looked at the following features.

Online Quote Availability

We scored this on a binary scale, awarding 1 point to companies allowing you to get a quote for term insurance online without contacting an agent, and 0 to companies that don’t. We awarded another point to companies that offered online quotes for no-medical-exam policies.

The ability to get quotes online is important because it allows you to easily compare quotes and understand your costs.

Online Application Availability

We scored this on a binary scale, awarding 1 point to companies offering an online application and 0 to companies that don’t.

Consumers should be able to buy insurance online, just like they can with other goods and services, without needing to contact an agent or sales representative first.  

Online Claim Availability

We scored this on a binary scale, awarding 1 point to companies offering the ability to initiate a life insurance claim online, either on a website or via email, and 0 to companies that don’t.

While the person buying life insurance will likely not be filing a life insurance claim in the future, ideally, their beneficiaries have a convenient online option for doing so, which is especially important when they might be grieving.

Same-Day Decision Availability

We scored this on a binary scale, awarding 1 point to companies offering the ability to be approved for a life insurance policy within a day, and 0 points to companies that don’t.

The availability of same-day decision policies is important for people seeking financial protection without a lengthy underwriting process, either because of convenience or because they wouldn’t qualify for traditional policies. 

Live Customer Service Chat

We scored this on a binary scale, awarding 1 point to companies with a chat function on their website that connects you with a human representative (not a robot), and 0 points to companies that don’t.

Live chats are a great customer support and accessibility feature, allowing people to get real-time assistance with their questions and concerns.

A company that offers more policy types can better meet diverse customer needs and provide tailored coverage options. 

We checked whether insurance companies had the following policy types:

• Term life insurance
• Money back, return-of-premium (ROP) term life
• Term life with annual renewal
• Whole life insurance
• Final expense or burial insurance for whole life
• Dividend-paying whole life
• Children’s whole life
• Universal life insurance
• Indexed universal life
• Variable life or variable universal life
• Joint or first-to-die life insurance
• No-medical-exam life insurance

We awarded 1 point for each policy type a company offered. If a company was missing a policy type, it got 0 points for that policy type.

Digging deeper, we looked at each company’s specific policy features and riders. These provide insight into the flexibility and comprehensiveness of coverage options.

Term Insurance Minimum Coverage Amount

We scored this on a continuous scale of 0 to 1, such that companies with the lowest minimum coverage amounts received a higher score and companies with a higher minimum coverage amount received a lower score. Globe Life had the lowest term life death benefit requirement at $5,000, while companies such as Securian, Minnesota Life, and Symetra required at least a $250,000 death benefit.

A low minimum coverage amount is important for consumers who may have a limited budget for financial protection.

Term Life Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, such that companies with the highest maximum coverage amounts received a higher score and companies with a lower maximum coverage amount received a lower score. Several companies don’t impose a cap on the total death benefit amount, but among those that do, Globe Life had the lowest maximum at $100,000.

A high maximum coverage amount is important for consumers to ensure they get all the financial protection they need from their policy.

Term Insurance Maximum Issue Age

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum issue age receiving a higher score and companies with a lower maximum issue age receiving a lower score. Globe Life had the highest maximum issue age of 90 years, while companies including Lincoln Financial and Equitable only offer term policies for individuals up to age 60.

Higher age limits are important for consumers who might want coverage later in life.

Maximum Term

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum terms receiving a higher score and companies with a lower maximum term receiving a lower score. Protective and Banner Life offer term lengths of up to 40 years, the highest among the companies we researched. Globe Life had the most limited term length offerings with a maximum of five years.

A variety of term lengths allows consumers to find coverage that aligns with their specific needs. 

Term Life Insurance With Conversion

We scored this on a binary scale, awarding 1 point to companies that offer term life policies that can be converted to permanent policies, and 0 points to companies that don’t. We awarded an additional point if companies offered conversion with no additional cost.

Convertible term life insurance allows policyholders to convert their term policy into a permanent policy without undergoing additional medical underwriting, which could be a good option for policyholders whose financial needs may change later in life.

Whole Insurance Minimum Coverage Amount

We scored this on a continuous scale of 0 to 1, such that companies with the lowest minimum coverage amounts received a higher score and companies with a higher minimum coverage amount received a lower score. Companies including Protective and Transamerica issue whole life policies with coverage as low as $1,000. Brighthouse Financial had the highest minimum coverage amount at $250,000.

Whole Life Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, such that companies with the highest maximum coverage amounts received a higher score and companies with a lower maximum coverage amount received a lower score. Several companies do not have a coverage maximum, but among those that do, the lowest was Colonial Penn at $25,000.

Whole Life Maximum Issue Age

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum issue age receiving a higher score and companies with a lower maximum issue age receiving a lower score. MassMutual, Thrivent, and Guardian Life had the highest maximum issue ages; all three issue whole life policies for individuals up to age 90. Aflac had the lowest limit for whole life issue age, only offering policies up to age 70.

Whole Life Insurance Dividend Rate

We scored this on a continuous scale from 0 to 1, where companies with higher dividend rates received a higher score and companies with lower or no dividend rates received a lower score. 

MassMutual’s 6.1% dividend interest rate (as of July 2, 2024) was the highest among all companies we researched.

Universal Insurance Minimum Coverage Amount

We scored this on a continuous scale of 0 to 1, such that companies with the lowest minimum coverage amounts received a higher score and companies with a higher minimum coverage amount received a lower score. Many companies shared the lowest minimum coverage amount for universal life policies at $25,000. Northwestern Mutual had the highest minimum coverage requirement, at $250,000. 

Universal Life Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum coverage amounts receiving a higher score and companies with a lower maximum term receiving a lower score. Several companies offer universal life policies with no specified maximum, but among those that have a limit, Columbus Life had the lowest maximum coverage amount at $100,000. 

Universal Life Maximum Issue Age

We scored this on a continuous scale of 0 to 1, with companies with the highest maximum issue age receiving a higher score and companies with a lower maximum issue age receiving a lower score. John Hancock had the highest maximum issue age for universal policies, issuing policies up to age 90. Penn Mutual had the lowest maximum issue age, at 71 years old. 

No-Medical-Exam Policy for Universal Life

We did not score this category, but we collected this data to help judge the best companies for universal life insurance.

Burial Insurance Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, with companies with the highest maximum coverage amounts receiving a higher score and companies with a lower maximum term receiving a lower score. The highest burial life coverage amount was $50,000, offered by companies including Nationwide and Lafayette Life. State Farm offered the lowest death benefit amount for burial insurance at $15,000.

Burial Insurance Minimum Issue Age

We scored this on a continuous scale of 0 to 1, such that companies with the lowest minimum issue age received a higher score and companies with a higher maximum issue age received a lower score. Nationwide and Transamerica are the least restrictive regarding issue age for burial insurance, as anyone can apply and receive coverage starting at birth. Other companies—such as SBLI, Foresters, and Gerber Life —require applicants to be at least 50 years old to qualify for a policy.

Lower age limits are important for consumers who want to guarantee coverage while they’re young.

Burial Insurance Maximum Issue Age

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum issue age receiving a higher score and companies with a lower maximum issue age receiving a lower score. The lowest maximum issue age was 80 years old, and was shared across companies such as Nationwide, State Farm, and Farmers. The highest maximum issue age was 85 years old, offered by SBLI, Lafayette, and USAA. 

Burial Insurance Graded Benefit Period

We scored this on a continuous scale of 0 to 1, where companies with the shortest graded benefit period received a higher score and companies with the longest graded benefit period received a lower score. The highest graded benefit period was three years, including companies such as SBLI, Fidelity Life, and Lafayette. The lowest-graded benefit period was two years, shared by many companies that offer burial insurance.

During the graded period, which typically lasts two to three years, the full death benefit is not paid out if the insured person dies, so a shorter graded period is typically better for beneficiaries.

No-Medical-Exam Insurance Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, where companies with the highest maximum coverage amounts received a higher score and companies with a lower maximum term received a lower score. 

We awarded an extra 1 point to companies who offered at least $50,000 in coverage for no-medical-exam life insurance. 

Banner Life has no specified maximum on its no-medical-exam policies, allowing beneficiaries to get the highest possible death benefit across the companies we researched. The lowest death benefit maximum was $25,000, offered by Mutual of Omaha, Colonial Penn, and New York Life through AARP. 

Coverage for People with Diabetes

We scored this on a binary scale, awarding 1 point to companies that cover people with diabetes and 0 to companies that don’t.

Health status is a key factor in how much you pay for life insurance. If a life insurance company offers coverage for people with diabetes, it’s a sign that the insurer is flexible and inclusive when it comes to medical underwriting.

Offers Diabetes Management Tools

We scored this on a binary scale, awarding 1 point to companies that offer diabetes management tools and 0 to companies that don’t.

Diabetes management tools, which may help monitor blood glucose levels, medication adherence, and overall health, demonstrate a life insurer’s commitment to supporting the health of its policyholders.

Coverage for Cancer Survivors in Remission

We scored this on a binary scale, awarding 1 point to companies that offer regular (not no-exam or guaranteed issue) coverage to cancer survivors in remission and 0 to companies that don’t.

Cancer survivors often have difficulty securing life insurance coverage. If a life insurance company offers coverage for cancer survivors in remission, it’s a sign of that insurer’s flexibility and inclusiveness when it comes to medical underwriting.

It’s important to understand which riders are available to purchase and which are automatically included in your policy because it can help you better compare quotes and decide which policy best fits your needs.

For each company, we collected data on whether it offered the following types of riders:

• Spouse rider
• Guaranteed insurability rider
• Waiver of premium rider
• Disability income rider
• Accidental death benefit
• Terminal illness rider
• Long-term care rider
• Chronic illness rider
• Critical illness rider
• Child term rider

We awarded 1 point if the company offered the rider, and 0 points if it didn’t.   

We awarded an extra point (up to a total of four) for including the following riders at no additional cost:

Child Whole Life Maximum Coverage Amount

We scored this on a continuous scale of 0 to 1, with companies that had the highest maximum coverage amounts receiving a higher score and companies with a lower maximum term receiving a lower score. A few companies on our list offer child whole life policies with no specified maximum. These include Nationwide, MassMutual, and Penn Mutual. Globe Life offered the lowest maximum coverage amount, at $30,000.

Ability to Convert Child Term Rider to Permanent Coverage

We scored this on a binary scale, awarding 1 point to companies with child term riders that can be converted to a permanent policy and 0 to companies that don’t.

A convertible child term rider ensures that an insured child can continue to have coverage in the future, regardless of health changes.

Ability to Transfer Child Policy to Child at Adulthood

We scored this on a binary scale, awarding 1 point to companies that allow parents to transfer child policies to their children once they reach adulthood and 0 to companies that don’t.

Transferable child policies ensure that an insured child can continue to have coverage once they reach adulthood, regardless of health changes.

Child Term Rider Maximum Coverage Age

We scored this on a continuous scale of 0 to 1, with companies that had the highest coverage issue age receiving a higher score and companies with a lower coverage issue age receiving a lower score. Companies such as Protective, Banner, Transamerica, and USAA provide coverage through the child term rider up until age 25, the highest amount we recorded across 45 companies. Other companies—including Penn Mutual, Prudential, and State Farm—only covered children through the child term rider until age 17.

Higher coverage ages are important for consumers who want to maintain coverage for their children for as long as possible.

Child Term Rider Minimum Coverage Age

We scored this on a continuous scale of 0 to 1, with companies with the lowest coverage issue age receiving a higher score and companies with a higher minimum coverage issue age receiving a lower score. Most companies set a minimum coverage age of 15 days, though some, including Lafayette and Penn Mutual, can start coverage at birth or adoption.

A high frequency of complaints can indicate that an insurance company has problems responding to customer needs. The National Association of Insurance Commissioners (NAIC) is a regulatory organization that maintains a database of complaints filed against insurance companies. With this data, the NAIC creates an index that conveys how many complaints an insurance company has received relative to how many complaints it’s expected to receive based on its market share. We averaged each company’s NAIC index over three years.

If a company receives fewer complaints than expected, its index is less than 1. An index of 0 means the company received no complaints. An index greater than 1 means the company received more complaints than expected. Some examples of types of complaints are delays in benefit payment, poor claim handling, and claim denials.

Using the NAIC Complaint Index, we calculated a three-year weighted average NAIC score for each company’s total premiums and index values from 2021-2023. Our three-year average was scored on a continuous scale from 0 to 1, where the company with the lowest NAIC index, Northwestern Mutual, received a score of 1, and the one with the highest, Mutual Trust Life Solutions, received a score of 0. Thrivent, MassMutual, Pacific Life, and Guardian also stood out for their strong customer satisfaction scores.

We also considered J.D. Power’s customer satisfaction scores and rankings for individual life insurance companies. The consumer insights firm surveyed 5,588 individual life insurance customers for its 2023 study. We did not score the results because they did not cover all the companies in our review, but we took them into account for editorial purposes.

Comparing quoted premiums across different insurers helps identify which companies offer the most cost-effective coverage for the desired policy type and amount. 

We researched quotes from each company for men and women in different age groups in excellent health for a $250,000, 30-year term policy. We used the following factors to run quotes for six different sample applicants:

• ZIP codes: 90011 and 77084
• Birthdays: Nov. 1, 1999, 1984, and 1969 (ages 25, 40, and 55)
• Health: Exceptional
• No medications
• No negative family health history
• 30-year term
• Coverage amount of $250,000

For each unique persona, we scored premium values on a range from 0 to 1 (0 being the most expensive policies; 1 being the least expensive). For each company, we averaged the scores across all personas to create a composite cost score.

We used a separate sample for older adults (ages 55 and 65), since they face more difficulty getting affordable coverage and are likely to get shorter terms:

• Birthdays: Nov. 1, 1969 and 1959
• Length of coverage: 20-year-term for 1969 birth year, 15-year term for 1959 birth year
• Coverage amount: $250,000

Life insurance is an essential financial topic for our readers, and we’ve written extensively about it. We have articles about the best life insurance companies for specific products or to meet the needs of particular readers. 

The research conducted and the data collected to create this methodology have been used to compile the following list of recommendations:

• Best Life Insurance Companies
• Best Term Life Insurance Companies
• Best Whole Life Insurance Companies
• Best Universal Life Insurance Companies
• Best Life Insurance Companies for People Over 50
• Best No-Medical-Exam Life Insurance
• Best Children’s Life Insurance Companies

Meet the Life Insurance Research & Reviews Team

Shanker narayan, yasmin ghahremani.

Yasmin Ghahremani is an Associate Editorial Director at Investopedia, where she oversees educational content about consumer financial products, ranging from checking accounts to life insurance. She joined the team in January 2023, after working for nearly four years in a similar role at The Balance. She has more than a decade of experience educating consumers about personal finance, which also includes stints as a managing editor at CreditCards.com and Wise Bread, and a contract editor at LendingTree.

Yasmin has also had an extensive international career covering business, technology, and the environment for broadcast and print outlets, including CNN, CNBC, and Asiaweek magazine. She has a Master of International Affairs degree from Columbia University.

Isaac Braun

AM Best. “ About Us .”

AM Best. “ Guide to Best’s Financial Strength Ratings .”

National Association of Insurance Commissioners. “ Results by Complaint Index .”

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• Published: 13 August 2024

Disability-related disparities in health outcomes among newly diagnosed diabetic patients: A retrospective cohort

• Sujin Kim 1 &
• Boyoung Jeon 2  

BMC Public Health volume  24 , Article number:  2207 ( 2024 ) Cite this article

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A distinct gap in the literature persists regarding the health outcome of individuals with Type 2 diabetes who also have disabilities. This study aimed to investigate potential disparities in events occurrence among diabetes patients across various disability stages.

We conducted a retrospective cohort study on patients newly diagnosed with diabetes in 2013 and 2014, aged ≥ 18 years, and followed them until December 2021, using data from the Korean National Health Insurance database. All-cause mortality and hospitalization for diabetes mellitus and cardio-cerebrovascular diseases (CVD) was assessed.

The study included 26,085 patients, encompassing individuals without disabilities and those with physical, visual, hearing and speech, intellectual and developmental, and mental disabilities. After adjustment, individuals with disabilities had a higher risk of all-cause death (adjusted hazard ratio [aHR]: 1.25, 95% CI: 1.07–1.48) compared to those without disabilities. In particular, severe disabilities and hearing and speech disabilities showed significantly higher risks of all-cause death (aHR: 1.40, 95% CI: 1.06–1.85 and aHR: 1.58, 95% CI: 1.17–2.15, respectively), with marginal significance for mild disabilities (aHR: 1.20, 95% CI: 0.99–1.45) and mental disorders (aHR: 1.92, 95% CI: 0.98–3.73). Patients with disabilities also had significantly increased risks of CVD-related first admissions (aHR: 1.30, 95% CI: 1.07–1.56) and diabetes-related first admissions (aHR: 1.31, 95% CI: 1.20–1.43) compared to those without disabilities.

Conclusions

This study underscores the urgent need for public health policies to prioritize individuals with disabilities and diabetes, addressing the disparities in health outcome.

Peer Review reports

The global prevalence of diabetes among the 20–79 year old demographic in 2021 was estimated at 10.5%, encompassing approximately 530 million people, with Type 2 diabetes accounting for over 90% of cases worldwide [ 1 ]. This epidemic is responsible for 6.7 million deaths worldwide and increases the risk of cardiovascular disease and mortality [ 2 ]. Concurrently, 1.3 billion people, constituting 16% of the global population, living with significant disabilities [ 3 ], among whom a higher prevalence of diabetes is observed. Given well-documented disability-related health inequalities [ 3 ], the burden of diabetes is particularly pronounced among persons with disabilities. Factors such as harmful behavior, limited access to healthy diets, and quality care, as well as delayed detection, may exacerbate this burden [ 4 ]. In addition, persons with disabilities may exhibit poor compliance with medical treatment due to physical limitations, socio-economic conditions, as well as hard to finding adequate physicians heightening the risk of diabetes complications and mortality [ 5 , 6 , 7 ].

While an existing study has reported an association between disabilities and poor health outcome among diabetic patients, it only focused on vision impairments and hearing disorders and fail to differentiate between disabilities caused by diabetes itself. Although patients with diabetes have a higher risk of death and hospitalization, the nuanced landscape of disability-related health inequalities has been overlooked among diabetic patients [ 8 ]. Furthermore, although an emerging body of literature has highlighted the importance of continuity of care (COC) and medication adherence in reducing diabetes-related complications and mortalities [ 9 ], their impact on the health outcomes of persons with disabilities and diabetes remain inadequately explored [ 10 , 11 , 12 ].

Despite existing research on health outcome of individuals with disabilities attributed to diabetes, a distinct gap in the literature persists with respect to comparisons based on disability itself, as well as its characteristics and types. In addition, studies integrating the elements of COC and medication adherence (proportion of days covered, PDC) into their analysis remain considerably limited. Addressing this gap is essential for understanding the health outcomes of persons with disabilities and diabetes and developing effective interventions. Thus, this study aimed to investigate potential disparities in the occurrence of fatal and non-fatal events among patients with diabetes across various stages of disability, while examining the influence of factors such as continuity of care and medication adherence. Utilizing national cohort data from the Korean National Health Insurance Service (NHIS) database, we specifically aimed to explore the association of disability status, severities, and types with mortality among adults with Type 2 diabetes, as well as hospitalization due to diabetic and cerebrovascular diseases (CVD).

Database and study population

The study population was derived from the NHIS database. The NHIS provides mandatory health care coverage for almost all Koreans, including National Health Insurance (NHI) enrollees (97%) and Medical Aid beneficiaries (3%), and covers most forms of health services, including emergency, inpatient and outpatient care, and medication prescriptions. The NHIS database contains the insurance claims of medical institutions and enrollee information, including disability type and severity, health coverage type, NHI contributions, and death records. A key advantage of the NHIS is that it is managed by a single insurer under the government, ensuring the databases includes nearly all medical use information recorded during the claims process [ 13 ].

For this study, 10,413,089 participants, representing 20% of the 2012 population, were sampled considering the sex, age, and region distribution from the NHIS database, which contains the insurance claims of medical institutions and enrollee information. We collected data from the NHIS database between January 2012 and December 2021 (data number: NHIS-2022-1-629) [ 13 ]. Disability status, including primary type of disability and severity of disability, health coverage type, and NHI contributions, was examined as of January of each year. Because this study used de-identified data provided by the NHIS after anonymization according to strict confidentiality guidelines, the requirement for ethics review was exempted by the Institutional Review Board (IRB) of Korea Institute for Health and Social Affairs (IRB number: 2022-004).

We defined the study population as newly diagnosed diabetes (E12) patients aged ≥ 18 years in 2014 and 2015, excluding those with internal organ impairments and epilepsy disability (who are more likely to be hospitalized unavoidably due to the disability itself) and those with facial disfigurement (a low proportion). Patients with newly diagnosed diabetes did not visit healthcare institutions for type 2 diabetes (E11) during the previous two years, but did visit with a diabetic diagnosis code in 2014 or 2015 with an oral antihyperglycemic prescription according to the International Classification of Disease 10th revision codes. The inclusion criteria included patients with a primary diagnostic code while the exclusion criteria included those with a whole diagnostic code. Among 31,331 newly diagnosed diabetic patients, we excluded 3,949 subjects who had medical records of CVD (I20-I25, I60-I64, I67 and I69) for the two years before the diagnosis. We also excluded 447 patients with diabetes who were hospitalized for 90 days or longer during the two years immediately after the diagnosis, which reflects a serious condition and affects PDC and COC assessment [ 12 ]. Then, 379 patients with diabetes were excluded because of missing values for the covariates. Finally, we excluded patients who experienced each event during the first two years depending on dependent variables (Fig.  1 ). All participants were followed from diagnosis until the outcome event or December 31, 2021, whichever came earliest.

Study population

Classification of disabilities

The level of disability was categorized into mild and severe according to the Ministry of Health and Welfare (MOHW) definition. We included eight types of disability based on the MOHW definition and categorized them into the following five groups: (1) physical disability–orthopedic impairment and brain injury; (2) visual disability; (3) hearing and speech disability; (4) intellectual and developmental disability–intellectual disability and autism spectrum disorder; and (5) mental disability (schizophrenia, schizoaffective disorder, bipolar affective disorder, recurrent depressive disorder, organic psychiatric disorder due to neurological damage, obsessive-compulsive disorder, Tourette’s disorder, and narcolepsy) [ 14 ].

COC and PDC variables – modifying factors

We calculated the COC and PDC during the 2 years after the diagnosis to ensure longitudinal continuity and medication adherence. First, we used the Bice–Boxerman continuity of care index score (COCI), which is influenced by the distribution of visits to different healthcare providers, i.e., the total number of visits, total number of providers, and number of visits with each provider. This index measures the degree to which patients visit several providers by counting the total number of visits (N), the total number of visits to the i th provider ( \(\:{n}_{i}\) ), and the total number of providers (j) using the following formula:

The COCI has a value between 0 and 1, with 1 indicating that all visits were to the same provider and 0 indicating full discontinuity of care. In this study, providers were defined as healthcare institutions.

Next, we assessed medication adherence using the PDC, the recently preferred method of measuring medication adherence [ 12 , 15 , 16 ]. The PDC was calculated based on the Anatomical Therapeutics Chemical (ATC) Code. Oral antihyperglycemic agents included biguanides (A10BA), sulfonamides, urea derivatives (A10BB), combinations of oral blood glucose-lowering drugs (A10BD), α-glucosidase inhibitors (A10BF), thiazolidinediones (A10BG), dipeptidyl peptidase 4 (DPP-4) inhibitors (A10BH), and other blood glucose-lowering drugs, excluding insulin (A10BX) [ 10 , 12 ].

Although people with disability may have limited access to regular care, at least four and two visits are essential for calculating the COC and PDC, respectively. Thus, we created a combined variable of COC and PDC (COC–PDC), defining values ≥ 0.8 as high COC and high PDC, and classified them into five categories, creating another category for subjects with four or fewer visits: four or fewer outpatients visits, low COC and low PDC, high COC and low PDC, low COC and high PDC, and high COC and high PDC.

Confounding factors

Age, sex, health coverage type, income, and comorbidities were included as covariates. Age was employed as a continuous variable with age square. Healthcare coverage included NHI enrollees and Medical Aid (a subsidy program for the poor). Income level was categorized into the following five groups using contribution quintiles: Medical Aid and first, second, third, fourth, and fifth contribution quintiles. We calculated the Charlson Comorbidity Index (CCI) using the primary diagnosis codes in healthcare use records from 2018 to evaluate the level of comorbidities (0, 1, 2, or ≥ 3), referring to the definition of Charlson and colleagues [ 17 ].

The primary outcome was all-cause mortality. The secondary outcomes were hospitalization for diabetes for patients with diabetes and CVD. Hospitalization was determined when patients received medical services as inpatients with a primary diagnosis code for diabetes (E11) and CVD (cardiovascular: I20-I25 and stroke: I60-I64, I67, I69). All outcomes were recorded as dichotomous variables.

Statistical analysis

The chi-square test and analysis of variance were conducted for categorical and continuous variables, respectively, to compare the differences in the baseline distributions of covariates by disability status, severity and types. Multivariate Cox proportional hazard regression analyses with competing risk models were conducted to evaluate adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for outcomes. The proportional hazard assumption was validated by including time-dependent covariates, which were created with interactions between the predictors and survival time, in the Cox proportional hazard regression models [ 18 ]. Stratified analyses of the association of disability types with outcomes were conducted according to the COC–PDC subgroups. All multivariate models were adjusted for the covariates listed above. Data analyses were performed using SAS Enterprise Guide 7.1 (SAS Institute, Cary, USA).

Characteristics of the study population

Table  1 shows that most participants had no disability (92.7%). Among those with disabilities, 67.8% had mild disabilities, and 32.2% had severe disabilities. The distribution of disabilities included physical (64.3%), visual (11.3%), hearing and speech (12.1%), intellectual and developmental (5.6%), and mental disabilities (6.7%). The average age of individuals without disabilities was 53.4 years, while those with disabilities had a higher mean age of 58.7 years. As for COC–PDC, 19.1% of those without disability had less than four outpatient visits while 34.0% had a high COC and PDC. In contrast, among those with disabilities, 20.0% had less than four outpatient visits and 37.1% had a high COC and PDC (Table  1 ). Supplementary Table 1 presents the characteristics of the study population for each event (Table S1 ).

Cox proportional hazards regression analysis

Table  2 presents the results of the Cox proportional hazard regression analysis for death, first admissions related to diabetes, and CVD. After adjusting for factors including sex, age, monthly contribution, insurance type, medical institution type, CCI score, and COC–PDC, individuals with disabilities showed a significantly increased risk of all-cause death (aHR: 1.25, 95% CI: 1.07–1.48) compared to those without disabilities. When differentiating disability severity, individuals with severe disabilities exhibited a significantly higher risk of all-cause death with aHR of 1.40 (95% CI: 1.06–1.85) compared to those without disabilities. Mild disabilities demonstrated a marginally significant increase in the risk of all-cause death (aHR: 1.20, 95% CI: 0.99–1.45). Patients with hearing and speech disabilities showed an increased risk of death (aHR: 1.58, 95% CI: 1.17–2.15) while those with mental disabilities did so with marginal statistical significance (aHR: 1.92, 95% CI: 0.98–3.73). Those with other disabilities did not exhibit a significant association (Table  2 ).

Patients with disabilities showed a significantly increased risk of CVD-related first admissions (aHR: 1.30, 95% CI: 1.07–1.56) compared to those without disabilities. Patients with diabetes with mild disabilities had an increased risk of CVD-related admissions (aHR: 1.30, 95% CI: 1.07–1.56), while those with severe disabilities showed no significant association (aHR: 1.28, 95% CI: 0.94–1.80). In addition, patients with visual disabilities, but not those with other disabilities, showed an increased risk of CVD-related first admissions (aHR: 1.59, 95% CI: 1.02–2.48) (Table  2 ).

Moreover, patients with diabetes and disabilities had an elevated risk of diabetes-related first admission compared to those without disabilities (aHR: 1.31, 95% CI: 1.20–1.43). Both mild and severe disabilities showed higher risks of diabetic hospitalization (mild: aHR: 1.22, 95% CI: 1.04–1.43; severe: aHR: 1.59, 95% CI: 1.22–1.50). In addition, patients with diabetes with physical, visual, and intellectual and developmental disabilities had an increased risk of diabetes-related first admission (aHR: 1.31, 95% CI: 1.17–1.46; aHR: 1.46, 95% CI: 1.15–1.84; and aHR: 1.70, 95% CI: 1.22–2.36, respectively), whereas those with hearing and speech disabilities and mental disabilities showed no significant association (aHR: 1.09, 95% CI: 0.77–1.55) (Table  2 ).

For explanatory analyses, we incorporated interaction terms between disability severity and COC–PDC groups, which were categorized into three groups: (1) the low COC-PDC group, representing four or fewer outpatient visits or low COC and low PDC; (2) the middle COC-PDC group, comprising high COC and low PDC or low COC and high PDC; and (3) the high COC-PDC group, characterized by both high COC and PDC. The low COC-PDC group was associated with an increased risk of diabetes-related first admission for individuals without disabilities (aHR: 1.09, 95% CI: 1.03–1.16), but not for those with mild or severe disabilities (aHR: 1.00, 95% CI: 0.79–1.26; aHR: 1.03, 95% CI: 0.73–1.45, respectively). Similar associations were found for CVD-related admissions and death, where the low and middle COC-PDC groups were significantly associated with increased risk for individuals without disabilities, but not always for those with disabilities (Fig.  2 ).

Association of COC-PDC with diabetes- and CVD-related hospitalization and mortality risk by disability severity

COC: continuity of care; CVD: Cardio-cerebrovascular disease; PDC: proportion of days covered

In this study, we examined the relationship between disability and the risk of all-cause death and admissions related to diabetes and CVD. After adjusting for COC and PDC, as well as demographic and health factors, individuals with disability were found to have an elevated risk of all-cause death compared to those without disability. In particular, individuals with severe disability exhibited a 40% increased risk of all-cause death compared to those without disability, while those with mild disability showed a less significant increase in risk. Among specific disabilities, hearing and speech impairments were associated with an elevated risk of death, with marginal significance observed for mental disabilities. For CVD-related admissions, mild and visual disabilities indicated an increased risk, whereas severe disability did not. The risk of diabetes-related admission remained elevated among persons with physical, visual, intellectual, and developmental disabilities. Our explanatory analyses showed that low COC-PDC was associated with a greater risk of all-cause death, diabetic and CVD hospitalization not consistently among those with disabilities.

In the present study, disability was associated with fatal results among newly diagnosed patients with diabetes, independent of major potential confounding factors. Considering that a large cohort study reported smoking and physical activity as the strongest predictors of death among patients with type 2 diabetes [ 19 ], a low physical activity rate among people with disabilities may be a significant risk factor for mortality among persons with disability and diabetes [ 20 ]. The heightened mortality risk observed among patients with diabetes and hearing and speech disabilities, as reported in this study, aligns with findings from previous research [ 8 , 21 ]. Prior studies have suggested that the simultaneous presence of hearing loss and diabetes may synergistically increase the risk of all-cause and CVD mortality. Furthermore, a recent systematic review highlighted potential mechanisms linking hearing loss to mortality, including aversion to physical activity, frequent falls, depression, anxiety, cognitive impairment, and social isolation [ 22 ]. Concerning mental disorders, existing literature has pointed out barriers to receiving appropriate care. These barriers include an inadequate training in health professionals, limited mental health literacy among non-mental health providers, and poor socio-economic conditions exacerbate these challenges [ 23 ]. These factors collectively may contribute to higher mortality rates among patients with diabetes and hearing and speech disabilities, as well as mental disabilities.

When we consider CVD hospitalization, patients with disability had an increased risk of CVD hospitalization. Furthermore, additional analyses showed a high risk of hospitalization due to ischemic heart disease in people with disability (Table S2 ). While body mass index, glycated hemoglobin and physical activity are significant risk factors for these events among persons with type 2 diabetes (19), persons with disabilities and diabetes are more likely to have uncontrolled diabetes and undesirable daily lifestyle choices. In the context of varying levels of disability severity, there was no significant higher risk of CVD hospitalization for severe disability, which differs from all-cause mortality. Patients with severe disability may face challenges in accessing hospitalization even for significant health conditions. For example, a previous examination on disability and incident coronary heart disease reported that disability was associated with fatal events, but not non-fatal events such as hospitalization due to angina pectoris or myocardial infarction [ 24 ]. This implies that health care disparities and the limited ability of persons with disability to cope with an acute event increases their risk of death.

In this study, an increased risk for CVD-related admissions but not all-cause mortality in persons with visual disabilities was partially consistent with a previous study that showed that vision impairments increase the risk of cardiovascular events and death in patients with type 2 diabetes [ 8 ]. In contrast, a previous study included any patients with diabetes and thus may have also included those with visual disabilities due to worsened diabetes, as well as those with worsened diabetes-related diseases [ 25 ]. Similar to the current study, a previous study showed that a visual acuity problem was not associated with diabetes-related mortality or longer-term all-cause mortality among patients with newly diagnosed type 2 diabetes [ 25 ].

Patients with diabetes with mild or severe disability had an increased risk of hospitalization. In addition, patients with physical, visual, intellectual, and developmental disabilities had a higher risk of diabetes-related hospitalization. Individuals with mental, intellectual/developmental, and physical disabilities showed a higher risk for avoidable hospitalizations for hypertension and diabetes-related conditions in Korea because they had access problems in primary care [ 6 ]. Persons with disabilities face a higher risk of adverse health outcomes due to barriers in accessing healthcare services and engaging in healthy behaviors. For example, previous studies have suggested that physical barriers to health screening or primary care access, difficulties in communicating with medical staff, and a lack of a healthy diet and regular exercise can lead to high rates of avoidable hospitalizations in these populations [ 6 ]. Another study indicated that visual acuity problems were not associated with diabetes-related mortality or longer-term all-cause mortality in patients with newly diagnosed type 2 diabetes [ 26 ].

The present study found a diminished significance of COC-PDC among individuals with disabilities, relative to their counterparts without disability. This is in contrast to the consistent evidence of COC and PDC in the management of type 2 diabetes in the general population. When we used the Usual Provider Index instead of COC, another frequently used measure to assess care continuance, the results remained similar (Table S3 ). One explanation for this discrepancy is that COC and PDC did not accurately reflect appropriate diabetic care in individuals with disability. Although previous studies consistently suggested that better COC may have positive effects on health outcomes by ensuring better information sharing and higher medication adherence [ 10 , 27 ], COC may not be linked to these positive benefits in patients with diabetes and disabilities. For example, a study on patients with diabetes with intellectual disability suggested that communication with health professionals about diabetes did not seem to occur [ 28 ]. In addition, although PDC represents the intention to treat and is directly linked to better medication adherence in the general population, individuals with disabilities are more likely to experience additional barriers to medication adherence. Even if individuals have been prescribed certain drugs, it does not confirm medication adherence or proper dosage management. They may not keep the proper frequency or dosage of medication at home because of a lack of health literacy or medication information provision [ 29 ]. This is particularly salient for persons with disabilities who need to manage complex and multimorbid conditions that may involve polypharmacy, thereby complicating medication adherence. Another explanation for the insignificant COC and PDC is the missed opportunity for early intervention to treat hyperglycemia, implement lifestyle changes, and address cardiovascular risk factors because of a delayed diagnosis of diabetes in individuals with disabilities. Inadequate care access and under-screening, both of which contribute to the prevalence of undiagnosed diabetes [ 30 , 31 ], have been reported in individuals with disability.

Therefore, rigorous further analysis is necessary to ensure the effectiveness of maintaining continuity of care and high medication compliance across different types and severities of disability in reducing hospitalizations and mortality. Tailored interventions for improving diabetes self-care among people with visual impairment (TID-VI) and the holistic, patient-centered Integrated Personalized Diabetes Management (iPDM) model hold promise for enhancing self-care and optimizing treatment outcomes [ 32 , 33 ]. To improve health outcomes and mitigate mortality risk among individuals with diabetes and disabilities, it is crucial to regularly manage blood glucose, blood pressure, cholesterol, and undergo annual screenings for complications. Lifestyle modifications, and adherence to necessary medications are also important [ 1 ].

Meanwhile, we excluded individuals with hospitalizations lasting 90 days or longer, potentially resulting in less pronounced associations within the subgroup of disabilities experiencing high hospitalization rates. Additional analyses incorporating these patients showed significant mortality and diabetic hospitalization and marginally significant CVD hospitalization for patients with mental disorders. We also found a significant high risk of mortality for persons with developmental disabilities when we included patients with long-term hospitalization (Table S4 ). This may be due to persons with severe conditions are more likely to be hospitalized; alternatively, the limited number of persons with these disabilities may weaken the statistical power. Future studies based on larger observations may improve our understanding. In our additional analysis, which included interaction terms between disability status encompassing both mild and severe disabilities and PDC-COC, we observed consistent results. Specifically, individuals with disabilities and high PDC-COC exhibited a lower risk of CVD hospitalization compared to those with low PDC-COC (Table S5 ). We acknowledge that studies with larger sample sizes would likely yield more robust results.

A notable limitation of the current study lies in its reliance on claims data analysis, which may not accurately capture the actual health behaviors of individuals with disabilities which can be potential influencing factors. For instance, although COC indicates regular interaction between patients and their physicians, the social support by family or caregivers of patients with severe disabilities may regularly visit physicians on the patient’s behalf to obtain medicine prescription, meaning that there is no continuous patient–physician interaction. In addition, the claims data also lack details on essential aspects of daily health management, such as levels of physical activity, exercise regimes, dietary habits, and blood glucose or HbA1c levels, which are critical determinants of health outcomes in this population. This study also could not include the specific information of the duration and the type of hospital admissions, such as emergency department visits. Future studies should address these limitations. Moreover, mental health conditions like depression could contribute to reduced patient interest in self-care practices [ 34 ].

This comprehensive study deepens our understanding of how disability status, severity, and various types of disabilities relate to the risks of all-cause death and hospitalization for diabetes and cardiovascular disease among newly diagnosed diabetes patients. Our findings underscore that individuals with disabilities face a heightened risk of all-cause death compared to those without disabilities, with particular emphasis on those with severe disabilities, hearing and speech impairments, and mental disabilities. In addition, physical, visual, intellectual, and developmental disabilities were associated with increased rates of diabetes-related hospitalizations, while mild and visual disabilities were associated with a higher risk of CVD-related admissions. Our results also highlight the role of COC-PDC, in that lower COC-PDC levels were identified as potential risk factors for adverse outcomes among individuals without disabilities, but less consistently so for those with disabilities. Therefore, public health policies should prioritize individuals with disabilities and diabetes to address the disparities in health outcomes between those with and without disabilities. Moreover, there is an urgent need for a better understanding of the unique risk factors for diabetes among persons with disabilities.

Data availability

The datasets analyzed during the current study are not publicly available due the restrictions apply to the use of data by NHIS. The use of current NHIS datasets is limited only for the permitted study and is not publicly available.

Abbreviations

Cardio-Cerebrovascular diseases

Continuity of care

Proportion of days covered

National health insurance service

Ministry of health and welfare

Continuity of care index score

Charlson comorbidity index

Adjusted hazard ratios

Confidence intervals

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This work was supported by the Korea Institute for Health and Social Affairs [research number 2022-33, 2022] and the National Research Foundation of Korea (NRF) [NRF-2022S1A5C2A03092307]. The funders had no role in the design or execution of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

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Boyoung Jeon

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S.K: Study conceptualization and design, data curation, formal analysis, methodology, writing – original draft, writing – reviewing and editing. B.J.: Study conceptualization and design, writing – original draft, writing – reviewing and editing.

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Kim, S., Jeon, B. Disability-related disparities in health outcomes among newly diagnosed diabetic patients: A retrospective cohort. BMC Public Health 24 , 2207 (2024). https://doi.org/10.1186/s12889-024-19690-5

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Received : 06 June 2024

Accepted : 05 August 2024

Published : 13 August 2024

DOI : https://doi.org/10.1186/s12889-024-19690-5

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