Apparent historical increases in autism are exaggerated because older cohorts are undercounted: many were never diagnosed in childhood, and higher mortality among severely affected autistics removes cases before adult surveys. Comparing today’s well‑ascertained children to yesterday’s sparsely diagnosed, partially deceased adults produces a misleading slope.
— This cautions policymakers and media against reading long‑run autism graphs as causal evidence and pushes for bias‑aware trend methods before funding or regulatory shifts.
Colin Wright
2025.12.03
72% relevant
The article uses the same logic applied in autism debates — that diagnostic practice, cohort ascertainment, and social visibility can create an apparent 'epidemic' — and applies it to transgender ID spikes (referring to rapid‑onset gender dysphoria and changes over 2008–2018), connecting to the idea that trends can be driven by measurement and drift rather than true incidence.
Cremieux
2025.10.15
70% relevant
The author lays out a liability–threshold decomposition using Swedish CATSS/NPR data to show increases in diagnosed autism can be explained by shifting diagnostic thresholds rather than true prevalence growth, consistent with the claim that observed trends reflect measurement/ascertainment effects.
2025.10.07
100% relevant
The article flags California Department of Developmental Services data and notes adult‑age ascertainment and shorter lifespans bias early cohorts downward.