Household-based screening methods reveal high-risk diabetes patterns across family units

New research presented at the Annual Meeting of the European Association for the Study of Diabetes (EASD) in Vienna, Austria (15–19 September) shows that early detection of individuals at risk of diabetes is possible by analyzing the electronic records of people living within the same household for risk factors.

The study is led by Dr. Tainayah Thomas, Stanford University, Palo Alto, CA, U.S., and colleagues.

Previous research indicates that a diabetes diagnosis within a family may improve health behaviors at the household level, since one person having diabetes may increase awareness of diabetes risk factors (such as obesity, high blood pressure and abnormal blood fats) in the household.

However, most of this research focuses on spouses/partners and on individuals with full-blown type 2 diabetes, and does not include other household members such as adolescent children or those at high risk for diabetes.

To assess household diabetes risk to support family-based diabetes prevention, in this new study the authors used electronic health record (EHR) and administrative data to identify household members, aged at least 10 years, of adult patients with prediabetes who are co-insured and reside in the same household to evaluate diabetes risk factors among household members.

This was a new study technique studying households of people with prediabetes—a state in which a person has an abnormal blood sugar profile, and would usually progress to full-blown diabetes without treatment and/or changes to their lifestyle.

Thus, it has the potential to focus on both stopping the index person progressing to type 2 diabetes, and detecting early risk in other household members. This is especially important given the rising incidence of diabetes among adolescents and young adults.

The researchers identified an index cohort of adults with prediabetes (fasting plasma glucose [FPG] 100–125 mg/dL or glycated hemoglobin 5.7–6.4% [39–46 mmol/mol]) and their co-insured household members in 2023.

The data used were from Kaiser Permanente Northern California (KPNC)—a large, integrated health care delivery system that provides primary and specialty care, outpatient and inpatient services, and pharmacy and laboratory services for some 4.5 million patients in Northern California, U.S..

Index cohort and household member characteristics, including demographics, enrollment, neighborhood, and health care utilization data including blood glucose screening tests were studied for both the index cases and their household members.

Age and sex-specific body mass index (BMI) for children/ young people aged 2–19 years was calculated using the Center for Disease Control’s (CDC) 2022 SAS program for CDC Growth Charts.

Diabetes risk factors were calculated for those children aged 10 years and older. The American Diabetes Association recommends risk-based screening for type 2 diabetes in children after the onset of puberty or aged 10 years who are living with overweight or obesity and have one or more additional risk factors for diabetes.

For adults aged 18 and older, diabetes risk factors were defined as: BMI of over 25 or a history of gestational diabetes, hypertension, abnormal blood fats, or cardiovascular disease; or, instead of these factors, prediabetes based on laboratory values. For children aged 10–17, diabetes risk factors were defined as overweight (age and sex-specific BMI in the top 15%) or obesity (age and sex-specific BMI in the top 5%).

Among 356,626 index adults with prediabetes, the mean age was 51 years, and 52% identified as female. The index cohort included 30% Non-Hispanic white, 28% Asian, 27% Hispanic, 9% Black, 1% Hawaiian or Pacific Islander, and 5% multiracial patients. Obesity was present in 59% of the index cohort.

Household composition varied, with 48% identified as one-person households and 52% living in multi-resident households. Over three quarters of multi-resident households (140,398) had at least one household member with additional diabetes risk factors. The authors identified 364,563 co-residing household members.

Of these, 238,247 were adults (aged 18 years and over) and 126,316 children aged 17 years and under. Of the children, 72,697 were aged 10–17 years. The mean age of adult household members was 42 years and 10 years for child household members.

Diabetes risk factors were identified in 65% of adults and 35% of children with overweight/obesity being the most identified risk factor present in 55% of adults and 34% of child household members aged 10–17 years.

An abnormal blood sugar profile was present in 32% of adult household members. In terms of absolute numbers, for adult household members, 48,297 (20% of adults) had a prediabetes laboratory (blood test) result and 28,997 (12% of adults) had blood test results showing full-blown type 2 diabetes.

A total of 285 child household members (less than 1% of children) had evidence of type 2 diabetes. Evidence of diabetes was assessed for household members 10–17 years using the health system’s diabetes registry—which puts a person on the register and records them as having diabetes but may not include blood test results, formal diagnosis or exclude the child as having type 1 diabetes.

For this study, the authors did not examine laboratory results for children and therefore did not identify prediabetes among them, although this is planned for future analyses.

While the study identified almost 30,000 adults showing full-blown type 2 diabetes living in the same households as adults with prediabetes, the authors explain the study cannot say whether or not they were already diagnosed.

“Of course, many of these people will have been diagnosed with prediabetes or type 2 diabetes, but a significant number could be unaware of their diagnosis and thus could be identified by our study,” explains Dr. Thomas.

“These are huge numbers of people identified with both prediabetes and type 2 diabetes. If even only a small proportion of these are newly diagnosed, this would make a significant public health impact.”

“For the children, parents might consider doing further tests in those cases where the children are living with overweight or obesity and have diabetes risk factors ,but have not yet been diagnosed. It is also, of course, an opportunity to make lifestyle changes to reduce the chances of metabolic complications in both adults and children.”

Dr. Thomas concludes, “To our knowledge, this novel study is the first to describe the use of electronic health record-based measures to assess household diabetes risk for adults with prediabetes. Our study highlights that diabetes risk is clustered within households, however, very few studies and health system prevention programs enroll households/families, reflecting a missed opportunity for population-level diabetes prevention.”

She adds, “All health systems could use this approach as a data-driven strategy to better and more systematically identify people at high risk for diabetes. This strategy could allow health systems to identify and tailor diabetes prevention messaging and programs to entire households instead of just individuals.”

The next steps planned by Dr. Thomas and her team include further investigations of household members, including if they assess follow-up care (diagnosis of diabetes or other conditions, enrollment in lifestyle interventions, and prescription of glucose-lowering medications).

Provided by
European Association for the Study of Diabetes

New research presented at the Annual Meeting of the European Association for the Study of Diabetes (EASD) in Vienna, Austria (15–19 September) shows that early detection of individuals at risk of diabetes is possible by analyzing the electronic records of people living within the same household for risk factors.

The study is led by Dr. Tainayah Thomas, Stanford University, Palo Alto, CA, U.S., and colleagues.

Previous research indicates that a diabetes diagnosis within a family may improve health behaviors at the household level, since one person having diabetes may increase awareness of diabetes risk factors (such as obesity, high blood pressure and abnormal blood fats) in the household.

However, most of this research focuses on spouses/partners and on individuals with full-blown type 2 diabetes, and does not include other household members such as adolescent children or those at high risk for diabetes.

To assess household diabetes risk to support family-based diabetes prevention, in this new study the authors used electronic health record (EHR) and administrative data to identify household members, aged at least 10 years, of adult patients with prediabetes who are co-insured and reside in the same household to evaluate diabetes risk factors among household members.

This was a new study technique studying households of people with prediabetes—a state in which a person has an abnormal blood sugar profile, and would usually progress to full-blown diabetes without treatment and/or changes to their lifestyle.

Thus, it has the potential to focus on both stopping the index person progressing to type 2 diabetes, and detecting early risk in other household members. This is especially important given the rising incidence of diabetes among adolescents and young adults.

The researchers identified an index cohort of adults with prediabetes (fasting plasma glucose [FPG] 100–125 mg/dL or glycated hemoglobin 5.7–6.4% [39–46 mmol/mol]) and their co-insured household members in 2023.

The data used were from Kaiser Permanente Northern California (KPNC)—a large, integrated health care delivery system that provides primary and specialty care, outpatient and inpatient services, and pharmacy and laboratory services for some 4.5 million patients in Northern California, U.S..

Index cohort and household member characteristics, including demographics, enrollment, neighborhood, and health care utilization data including blood glucose screening tests were studied for both the index cases and their household members.

Age and sex-specific body mass index (BMI) for children/ young people aged 2–19 years was calculated using the Center for Disease Control’s (CDC) 2022 SAS program for CDC Growth Charts.

Diabetes risk factors were calculated for those children aged 10 years and older. The American Diabetes Association recommends risk-based screening for type 2 diabetes in children after the onset of puberty or aged 10 years who are living with overweight or obesity and have one or more additional risk factors for diabetes.

For adults aged 18 and older, diabetes risk factors were defined as: BMI of over 25 or a history of gestational diabetes, hypertension, abnormal blood fats, or cardiovascular disease; or, instead of these factors, prediabetes based on laboratory values. For children aged 10–17, diabetes risk factors were defined as overweight (age and sex-specific BMI in the top 15%) or obesity (age and sex-specific BMI in the top 5%).

Among 356,626 index adults with prediabetes, the mean age was 51 years, and 52% identified as female. The index cohort included 30% Non-Hispanic white, 28% Asian, 27% Hispanic, 9% Black, 1% Hawaiian or Pacific Islander, and 5% multiracial patients. Obesity was present in 59% of the index cohort.

Household composition varied, with 48% identified as one-person households and 52% living in multi-resident households. Over three quarters of multi-resident households (140,398) had at least one household member with additional diabetes risk factors. The authors identified 364,563 co-residing household members.

Of these, 238,247 were adults (aged 18 years and over) and 126,316 children aged 17 years and under. Of the children, 72,697 were aged 10–17 years. The mean age of adult household members was 42 years and 10 years for child household members.

Diabetes risk factors were identified in 65% of adults and 35% of children with overweight/obesity being the most identified risk factor present in 55% of adults and 34% of child household members aged 10–17 years.

An abnormal blood sugar profile was present in 32% of adult household members. In terms of absolute numbers, for adult household members, 48,297 (20% of adults) had a prediabetes laboratory (blood test) result and 28,997 (12% of adults) had blood test results showing full-blown type 2 diabetes.

A total of 285 child household members (less than 1% of children) had evidence of type 2 diabetes. Evidence of diabetes was assessed for household members 10–17 years using the health system’s diabetes registry—which puts a person on the register and records them as having diabetes but may not include blood test results, formal diagnosis or exclude the child as having type 1 diabetes.

For this study, the authors did not examine laboratory results for children and therefore did not identify prediabetes among them, although this is planned for future analyses.

While the study identified almost 30,000 adults showing full-blown type 2 diabetes living in the same households as adults with prediabetes, the authors explain the study cannot say whether or not they were already diagnosed.

“Of course, many of these people will have been diagnosed with prediabetes or type 2 diabetes, but a significant number could be unaware of their diagnosis and thus could be identified by our study,” explains Dr. Thomas.

“These are huge numbers of people identified with both prediabetes and type 2 diabetes. If even only a small proportion of these are newly diagnosed, this would make a significant public health impact.”

“For the children, parents might consider doing further tests in those cases where the children are living with overweight or obesity and have diabetes risk factors ,but have not yet been diagnosed. It is also, of course, an opportunity to make lifestyle changes to reduce the chances of metabolic complications in both adults and children.”

Dr. Thomas concludes, “To our knowledge, this novel study is the first to describe the use of electronic health record-based measures to assess household diabetes risk for adults with prediabetes. Our study highlights that diabetes risk is clustered within households, however, very few studies and health system prevention programs enroll households/families, reflecting a missed opportunity for population-level diabetes prevention.”

She adds, “All health systems could use this approach as a data-driven strategy to better and more systematically identify people at high risk for diabetes. This strategy could allow health systems to identify and tailor diabetes prevention messaging and programs to entire households instead of just individuals.”

The next steps planned by Dr. Thomas and her team include further investigations of household members, including if they assess follow-up care (diagnosis of diabetes or other conditions, enrollment in lifestyle interventions, and prescription of glucose-lowering medications).

Provided by
European Association for the Study of Diabetes