Why Most Risks Are Still a Question Mark

Lack of studies

We have reasonably good toxicity data on roughly 1% of the 80,000-plus chemicals registered for use in the United States. The other 99% exist in varying degrees of "we don't know yet" — some minimally studied, some examined only for a narrow set of endpoints like cancer but not endocrine disruption or neurotoxicity, some barely looked at at all.

Of the 2,500 chemicals that are used most (1 million pounds produced every year), 45% of these don’t have adequate toxicological data for how they affect you or wildlife.

This is a direct consequence of the regulatory gap: under TSCA, chemicals don't have to be proven safe before entering the market. The burden falls on the EPA to prove harm after the fact. The EU's REACH framework reverses this — manufacturers must demonstrate safety before use — which explains why substances banned in Europe remain common in the U.S. The absence of evidence of harm is not the same as evidence of absence of harm, but in practice it often functions that way. With around 7 new chemicals introduced every single day,

Mixtures

The mixture problem compounds this further. Even for chemicals we do understand individually, we have almost no data on what they do in combination. You aren't exposed to one chemical at a time — you're exposed to dozens simultaneously, from your mattress, flooring, cookware, air, and personal care products. Those interactions can be additive, synergistic, or antagonistic, and we don't know which applies to most combinations you're actually encountering. As EFSA acknowledged in 2019, a comprehensive framework for characterizing the uncertainties of combined exposure to multiple chemicals does not yet exist.

Proprietary Ingredients

Most

This means that for the vast majority of chemicals in everyday products, dose-response data doesn't exist. We don't know where the curve is, what shape it takes, or what levels are safe — because no one has been required to find out. This isn't a conspiracy. It's a structural gap in the regulatory framework.

Exposure: We Don't Know How Much You're Actually Getting

Even when a chemical's hazard profile is reasonably well understood, calculating your actual exposure is its own problem. Product formulations are almost never disclosed in full. The foam in your couch, the coating on your pan, the treatment on your carpet — the specific chemicals and their concentrations are proprietary. You can't calculate exposure from a product you can't characterize.

Tier 1 includes foam and keyboards to remind people that just because non-toxic world focuses on buyable items and certain products, we deal daily with a lot of toxic products that we can't replace. This is important because it also strengthens my argument for the unknown chemical mixtures and level of exposure, dose, etc that I address in section 7. I don't want to freak people out, but it's important to know we tolerate a lot of toxic items and don't even notice. The only difference is that for one (keyboards, car seats), no healthy alternatives exist so you have to manage it."

This is not a theoretical problem. I wore a silicone monitoring wristband for an exposomics research study and was genuinely surprised by what I'd been exposed to — chemicals I hadn't thought about, from sources I wouldn't have predicted. Wearable biomonitoring is still a research tool, not a consumer product, which means most people have no way to measure their actual daily exposure load. The inputs to your personal risk calculation are largely invisible.

Dose: Body Burden Accumulates Over Time

Standard risk assessments treat exposure as a relatively stable variable — a daily dose you're receiving more or less consistently. For many chemicals this is a reasonable approximation. For persistent chemicals, it isn't.

Persistent bioaccumulative chemicals — PFAS, certain flame retardants, PCBs, heavy metals — don't clear quickly. They accumulate in fat tissue, bone, and organs over years and decades. What constitutes a "safe" daily dose is calculated against a baseline body burden, but that baseline is not zero for most adults. You are already carrying chemical exposures from years of prior contact, and that accumulated load interacts with current exposures in ways that standard dose calculations don't account for. A daily dose that looks inconsequential at 25 may not look the same at 55 — not because the dose changed, but because the baseline did.

Dose-Response: The Relationship Isn't Always What We Assume

The standard dose-response model assumes a threshold: below a certain dose, there is no effect. This is intuitive and it works reasonably well for many chemicals. It is also, for a meaningful category of substances, probably wrong — and the stakes around that wrongness are high.

Endocrine-disrupting chemicals are the clearest case. Because they work by mimicking or interfering with hormones, which operate at vanishingly small concentrations, they can produce effects at very low doses that disappear at higher doses — or produce different effects at different doses entirely. These non-monotonic dose-response curves don't fit the standard regulatory model, which means the safety thresholds set for endocrine disruptors may not actually be protective.

There's also an important political and economic dimension here. The threshold concept is not just scientifically convenient — it's commercially valuable. As epidemiologist David Michaels, former head of OSHA, has noted, within the scientific community the idea that there is a safe threshold for carcinogenic exposures is not widely accepted. But establishing a threshold is enormously useful for industry: if you can claim a threshold, you don't need to protect people at exposures below it. The pressure to maintain the threshold model in regulatory frameworks is not purely scientific.

We might also just have animal data!!! It doesn’t apply to humans for a few reasons.

Susceptibility: Timing Matters, and Some Effects Carry Forward

The standard approach to susceptibility accounts for individual variation — the 10x uncertainty factor in risk assessment exists partly to cover the range of human sensitivity. What it doesn't fully capture is developmental vulnerability, which operates differently from ordinary variation.

Fetuses, infants, and children are not just smaller adults. Their developing systems — neurological, endocrine, reproductive, immune — are undergoing rapid change and are meaningfully more sensitive to chemical disruption during those windows. Exposures during fetal development that would be inconsequential in an adult can have lasting effects on the developing brain, reproductive system, or hormonal axis. This is well established for lead, for example, and increasingly supported for a range of endocrine-disrupting chemicals. The regulatory frameworks that set acceptable exposure limits for adults are not always designed with these critical windows in mind.

More recently, research has suggested that some effects of chemical exposure may extend beyond the individual — that certain epigenetic changes triggered by exposures during development can be heritable, passed to children or grandchildren who were never directly exposed. This is still early science and the mechanisms are not fully characterized. But if it holds, it reframes the question considerably: "safe for me" becomes a more complicated calculation when some effects may not manifest until a generation later.

Risk: The Question Mark at the End

When a question mark sits on hazard, and another on exposure, and another on dose, dose-response, and susceptibility — the risk assessment at the end inherits all of them. The framework still produces something more useful than a guess. But it produces a probability range under conditions of significant uncertainty, not a clean answer.

Next up, in Part 8, you’ll see how irrationality adds even more chaos to the uncertainty. But, don’t worry, in Part 9, some order comes back. It’s important to wade through the mess first because it offers a deeper understanding that’s crucial to Parts 9, 10, and 11.

Understanding what we don't know, and why it's more useful than pretending we do.