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New analysis offered on the Annual Assembly of the European Affiliation for the Examine of Diabetes (EASD) in Vienna, Austria (15–19 September) reveals that early detection of people susceptible to diabetes is feasible by analyzing the digital data of individuals dwelling throughout the similar family for threat components.
The research is led by Dr. Tainayah Thomas, Stanford College, Palo Alto, CA, U.S., and colleagues.
Earlier analysis signifies {that a} diabetes analysis inside a household might enhance well being behaviors on the family stage, since one particular person having diabetes might improve consciousness of diabetes threat components (corresponding to weight problems, hypertension and irregular blood fat) within the family.
Nonetheless, most of this analysis focuses on spouses/companions and on people with full-blown sort 2 diabetes, and doesn’t embody different family members corresponding to adolescent kids or these at excessive threat for diabetes.
To evaluate family diabetes threat to help family-based diabetes prevention, on this new research the authors used digital well being document (EHR) and administrative information to establish family members, aged not less than 10 years, of grownup sufferers with prediabetes who’re co-insured and reside in the identical family to judge diabetes threat components amongst family members.
This was a brand new research method learning households of individuals with prediabetes—a state wherein an individual has an irregular blood sugar profile, and would often progress to full-blown diabetes with out therapy and/or adjustments to their way of life.
Thus, it has the potential to give attention to each stopping the index particular person progressing to sort 2 diabetes, and detecting early threat in different family members. That is particularly vital given the rising incidence of diabetes amongst adolescents and younger adults.
The researchers recognized 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 family members in 2023.
The info used had been from Kaiser Permanente Northern California (KPNC)—a big, built-in well being care supply system that gives major and specialty care, outpatient and inpatient providers, and pharmacy and laboratory providers for some 4.5 million sufferers in Northern California, U.S..
Index cohort and family member traits, together with demographics, enrollment, neighborhood, and well being care utilization information together with blood glucose screening exams had been studied for each the index instances and their family members.
Age and sex-specific physique mass index (BMI) for kids/ younger individuals aged 2–19 years was calculated utilizing the Middle for Illness Management’s (CDC) 2022 SAS program for CDC Progress Charts.
Diabetes threat components had been calculated for these kids aged 10 years and older. The American Diabetes Affiliation recommends risk-based screening for sort 2 diabetes in kids after the onset of puberty or aged 10 years who’re dwelling with obese or weight problems and have a number of further threat components for diabetes.
For adults aged 18 and older, diabetes threat components had been outlined as: BMI of over 25 or a historical past of gestational diabetes, hypertension, irregular blood fat, or heart problems; or, as an alternative of those components, prediabetes primarily based on laboratory values. For youngsters aged 10–17, diabetes threat components had been outlined as obese (age and sex-specific BMI within the prime 15%) or weight problems (age and sex-specific BMI within the prime 5%).
Amongst 356,626 index adults with prediabetes, the imply age was 51 years, and 52% recognized as feminine. The index cohort included 30% Non-Hispanic white, 28% Asian, 27% Hispanic, 9% Black, 1% Hawaiian or Pacific Islander, and 5% multiracial sufferers. Weight problems was current in 59% of the index cohort.
Family composition different, with 48% recognized as one-person households and 52% dwelling in multi-resident households. Over three quarters of multi-resident households (140,398) had not less than one family member with further diabetes threat components. The authors recognized 364,563 co-residing family members.
Of those, 238,247 had been adults (aged 18 years and over) and 126,316 kids aged 17 years and underneath. Of the youngsters, 72,697 had been aged 10–17 years. The imply age of grownup family members was 42 years and 10 years for baby family members.
Diabetes threat components had been recognized in 65% of adults and 35% of youngsters with obese/weight problems being probably the most recognized threat issue current in 55% of adults and 34% of kid family members aged 10–17 years.
An irregular blood sugar profile was current in 32% of grownup family members. By way of absolute numbers, for grownup family members, 48,297 (20% of adults) had a prediabetes laboratory (blood check) outcome and 28,997 (12% of adults) had blood check outcomes exhibiting full-blown sort 2 diabetes.
A complete of 285 baby family members (lower than 1% of youngsters) had proof of sort 2 diabetes. Proof of diabetes was assessed for family members 10–17 years utilizing the well being system’s diabetes registry—which places an individual on the register and data them as having diabetes however might not embody blood check outcomes, formal analysis or exclude the kid as having sort 1 diabetes.
For this research, the authors didn’t study laboratory outcomes for kids and subsequently didn’t establish prediabetes amongst them, though that is deliberate for future analyses.
Whereas the research recognized nearly 30,000 adults exhibiting full-blown sort 2 diabetes dwelling in the identical households as adults with prediabetes, the authors clarify the research can not say whether or not or not they had been already recognized.
“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 provides, “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 subsequent steps deliberate by Dr. Thomas and her group embody additional investigations of family members, together with in the event that they assess follow-up care (analysis of diabetes or different circumstances, enrollment in way of life interventions, and prescription of glucose-lowering medicines).
Extra data:
EASD 2025, Summary 7: T. Thomas, et al. Figuring out family diabetes threat for family-based diabetes prevention utilizing digital well being data
Supplied by
European Affiliation for the Examine of Diabetes
Quotation:
Family-based screening strategies reveal high-risk diabetes patterns throughout household items (2025, August 15)
retrieved 15 August 2025
from https://medicalxpress.com/information/2025-08-household-based-screening-methods-reveal.html
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