
Birth Weight, Childhood Weight Gain Linked to Non-Hodgkin Lymphoma Risk
Key Takeaways
- Greater birth weight (top vs bottom quartile) was associated with higher non-Hodgkin lymphoma risk, odds ratio 1.15 (P trend = .04).
- Weight when growth stopped showed the strongest signal: OR 1.30 for the heaviest vs lightest quartile (P trend < .001).
Mayo Clinic case-control study links higher birth weight and childhood obesity to greater non-Hodgkin lymphoma risk, while longer breastfeeding may lower odds.
Being born heavier and gaining more weight through childhood and adolescence were associated with greater odds of developing
Why Early-Life Exposures May Shape Later Lymphoma Risk
Non-Hodgkin lymphoma encompasses more than 100 lymphoid malignancy subtypes, and an estimated 79,320 new US cases were expected in 2025. Established risk factors include certain viral infections, family history of hematologic malignancy, immunodeficiency, and autoimmune disease, but many patients have no identifiable risk factor, keeping modifiable contributors a continued research focus.2
Researchers have theorized that perinatal and early-life exposures could shape adult lymphoma risk through a proinflammatory, immune-dysregulated environment and through altered lymphatic development tied to early antigen exposure. Adult
The case-control study enrolled 2280 patients with pathologically confirmed non-Hodgkin lymphoma and 2253 controls at Mayo Clinic Rochester between September 2002 and August 2014. A hematopathologist verified case classifications by World Health Organization criteria. The most common subtypes were
Perinatal and early-life exposures were self-reported at enrollment rather than drawn from birth or pediatric records. Participants recalled their birth weight, breastfeeding duration, and height and weight relative to peers at ages 7, 12, and 18, plus the age and weight at which growth stopped. The researchers used logistic regression to calculate odds ratios (ORs) and 95%CIs, adjusting for demographic and clinical confounders, and tested for linear trends and heterogeneity across 4 major non-Hodgkin lymphoma subtypes.
Birth Weight, Childhood Weight Gain Linked to Higher Non-Hodgkin Lymphoma Risk
After multivariable adjustment, the highest quartile of birth weight carried greater odds of non-Hodgkin lymphoma than the lowest quartile (OR, 1.15; P trend = .04). A similar pattern held for weight relative to peers at age 7 (OR, 1.05 for “heavy” and OR, 0.87 for “thin” vs average; P trend = .002) and for weight at the age growth ceased, where the heaviest quartile showed the highest odds relative to the lightest (OR, 1.30; P trend < .001).
None of these associations varied significantly by lymphoma subtype (P heterogeneity > .05 for all), and estimates held up in a sensitivity analysis excluding adult body mass index (BMI) from the models. The authors situated the findings within a broader literature linking higher adult BMI to non-Hodgkin lymphoma risk, including meta-analyses reporting relative risks of 1.05 to 1.12 per 5-kg/m² increase in BMI, framing their results as extending that adiposity hypothesis earlier into the life course.
Longer Breastfeeding Associated With Lower Risk
Compared with never being breastfed, breastfeeding beyond 6 months was associated with lower odds of non-Hodgkin lymphoma overall (OR, 0.77; 95% CI, 0.61-0.97) and of the CLL/SLL subtype specifically (OR, 0.63; 95% CI, 0.43-0.91). Breastfeeding for 1 to 6 months was also associated with ORs below 1, though neither that estimate nor the overall trend test reached statistical significance. Nearly half of participants had missing breastfeeding data, and missingness was not random with respect to several participant characteristics, warranting cautious interpretation of this finding.
“Greater body weight at birth and through childhood may be associated with increased NHL risk, potentially extending the life-course perspective on adiposity and lymphomagenesis, with implications for prevention,” the researchers wrote.
Proposed mechanisms behind a protective breastfeeding association include early immune tolerance, transfer of secretory immunoglobulin A through breast milk, and microbiome development via human milk oligosaccharides. The authors noted theirs is the first study of its kind with enough male participants and sample size to examine the most common non-Hodgkin lymphoma subtypes individually.
Recall Bias and Study Design Temper the Findings
As a case-control study, the research carries an inherent potential for recall and selection bias, a limitation the authors acknowledged directly. Self-reported exposures can introduce misclassification if cases and controls recalled early-life events with differing accuracy, and nonrandom missingness in breastfeeding data raised additional selection-bias concerns for that exposure. Residual confounding from unmeasured maternal or childhood factors could not be ruled out, and the population, drawn largely from Minnesota, Iowa, and Wisconsin and overwhelmingly non-Hispanic White, limits generalizability.
Because the analysis tested multiple exposures and subtypes, the authors characterized their results as hypothesis-generating, calling for replication in larger, prospective studies. That framing matters for how the findings should be read: they add a biologically plausible piece to the puzzle of early-life adiposity and feeding patterns in lymphomagenesis, but they do not yet translate into a screening tool, treatment implication, or payer policy lever. For now, the findings are most useful for guiding future non-Hodgkin lymphoma etiologic research, not for changing how clinicians or health systems manage risk today.
References
1. Cholack GA, Kleinstern G, Robinson DP, et al. Perinatal and early-life exposures and risk of non-Hodgkin lymphoma. Cancers (Basel). 2026;18(16):2666. doi:10.3390/cancers18162666
2. American Cancer Society. Non-Hodgkin lymphoma risk factors. Cancer.org. Accessed October 8, 2026.
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