What actually changes diabetes risk

The measured risk is real. In the MASALA and MESA studies, US South Asian adults aged 44 to 84 had an age-adjusted type 2 diabetes prevalence of 23%, compared with 6% in white adults [1]. That gap is documented and it matters. It is also not destiny. Flowers and colleagues analyzed the same data and found that body composition alone does not explain the difference [3]. The risk is partly unexplained, which means it is not fixed. This page collects what the published research actually reports about the factors that shift diabetes risk, each tied to its source, so you can separate a measured trial result from a listed risk factor and know what your clinician can act on.

What the Diabetes Prevention Program actually measured

The Diabetes Prevention Program followed people with prediabetes and measured concrete outcomes. NIDDK reports that in that trial, losing 5% to 7% of body weight lowered the chance of developing type 2 diabetes [5]. That is what the trial measured. It is not a promise that weight loss will prevent diabetes in any one person, and it is not a guarantee that the same result applies to everyone. It is a measured outcome in a specific group. Your clinician can discuss what it means for your situation.

No medication is FDA-approved specifically for preventing type 2 diabetes [6]. Medicines exist for managing blood glucose once diabetes is diagnosed, and the decision to use them belongs to a clinician who knows your full history. The trial result about weight loss is the strongest documented lever in the prevention space.

Why screening matters even when you feel fine

Most people with prediabetes have no symptoms [4][5]. The CDC states there are usually no signs when you have prediabetes, and most people who have it do not know [4]. That silence is why screening is a lever: it turns an unknown into a measured number. Once you know, you and your clinician can decide what to do next.

The American Diabetes Association recommends testing in adults with a BMI of 25 or higher, or 23 or higher in individuals of Asian ancestry, who have one or more additional risk factors [2]. Those risk factors include a first-degree relative with diabetes, a history of cardiovascular disease, hypertension, abnormal cholesterol or triglyceride levels, polycystic ovary syndrome, and physical inactivity [2]. If you fit that description, asking for a test is concrete and actionable.

The test itself is straightforward. An A1C test measures your average blood glucose over the past 3 months [5]. An A1C below 5.7% is normal, 5.7% to 6.4% is prediabetes, and 6.5% or higher is diabetes [2]. A single result is a snapshot, not a sentence. It is information you can bring to your clinician.

The risk factors that appear in multiple sources

The CDC and NIDDK both list risk factors for prediabetes and type 2 diabetes. They overlap, which means these are the factors the research keeps pointing to. Here is what they document:

Overweight or obesity appears in both lists [4][5]. Physical inactivity appears in both [4][5]. Age 35 or older appears in the NIDDK list and age 45 or older in the CDC list [4][5]. A family history of diabetes appears in both [4][5]. Smoking appears in the NIDDK list [5]. Polycystic ovary syndrome appears in the NIDDK list [5]. A history of gestational diabetes or delivering a baby weighing 9 pounds or more appears in both [4][5].

The CDC and NIDDK both note that Asian American people have a higher risk, with the CDC adding that some Pacific Islander people do as well [4][5]. The screening threshold of BMI 23 or higher for individuals of Asian ancestry reflects this measured elevation [2].

These are factors your clinician can discuss with you. Some of them, like physical inactivity and smoking, are things you can change. Others, like family history and age, are things you cannot. The point of listing them is not to frighten you. It is to give you and your clinician concrete ground to stand on.

What the research does not yet explain

Elevated risk in South Asian populations is measured and real [1]. It is also partly unexplained. Flowers and colleagues added detailed body composition measures to the MASALA and MESA analyses and concluded they did not identify strong evidence that accounting for body composition explains differences in the risk for type 2 diabetes [3]. That means the higher prevalence is not simply a story about weight distribution or muscle mass. Something else is at work, and it is not yet fully understood.

That uncertainty is important. It means the risk is not fixed or determined by factors already identified. It means screening and action matter even more, because the levers are not all identified yet. Your clinician is the person who can help you figure out which ones apply to you.

The documented levers in one table

Here are the factors that appear in published research, separated into what a trial measured and what risk-factor lists document:

What to do next

1. Ask your clinician whether you should be screened for prediabetes or diabetes. If you have a BMI of 23 or higher and one or more risk factors, the answer is likely yes [2].
2. If you get screened and the result is prediabetes or diabetes, write down the A1C number and the date so you can track it over time.
3. Ask your clinician about the Diabetes Prevention Program or a similar lifestyle program in your area. The trial measured that weight loss of 5% to 7% of body weight shifted the odds [5].
4. If physical inactivity is on your list, ask your clinician what kind of activity makes sense for you. The CDC and NIDDK both list it as a modifiable risk factor [4][5].
5. If you smoke, ask your clinician about support for quitting. NIDDK lists smoking as a risk factor for prediabetes [5].
6. Check the prediabetes at a normal weight guide if your screening result surprised you, and the South Asian diabetes risk guide for more on the measured elevation in your population.
7. Return to the guides hub for other screening and risk topics.

Sources

1. Kanaya and colleagues, MASALA and MESA diabetes prevalence, age-adjusted prevalence in US South Asian and other populations, accessed 2026-08-06, https://pubmed.ncbi.nlm.nih.gov/24705613/
2. American Diabetes Association, Diagnosis and Classification of Diabetes, Standards of Care in Diabetes 2026, screening thresholds and risk factors, accessed 2026-08-06, https://diabetesjournals.org/care/article/49/Supplement_1/S27/163926/2-Diagnosis-and-Classification-of-Diabetes
3. Flowers and colleagues, body composition and diabetes risk in South Asians, unexplained elevation in diabetes risk, accessed 2026-08-06, https://pubmed.ncbi.nlm.nih.gov/30796111/
4. CDC, diabetes risk factors, risk factor list and Asian American risk, accessed 2026-08-06, https://www.cdc.gov/diabetes/risk-factors/index.html
5. NIDDK, insulin resistance and prediabetes, Diabetes Prevention Program weight loss result and risk factor list, accessed 2026-08-06, https://www.niddk.nih.gov/health-information/diabetes/overview/what-is-diabetes/prediabetes-insulin-resistance
6. American Diabetes Association, Prevention or Delay of Diabetes, Standards of Care in Diabetes, FDA approval status for diabetes prevention medications, accessed 2026-08-06, https://pmc.ncbi.nlm.nih.gov/articles/PMC12690170/