I hope everyone is doing well.
Let $K \subset \mathbb{R}^n$ be a centrally symmetric convex body $(K = -K)$. Denote by $K \mid H$ the orthogonal projection of $K$ onto $H$, where $H$ is an $n - 1$ dimensional linear subspace. It is easy to see that the section $K \cap H$ is always contained in $K \mid H$ and therefore $\lambda(K \cap H) \leq \lambda(K \mid H)$, where $\lambda$ is the Lebesgue measure.
This leads to a natural question that I was thinking about today.
The problem is posed as follows:
Denote by $G(n - 1)$ the set of all $n-1$ dimensional linear subspaces of $\mathbb{R}^n$. Is it true that for every convex body $K \subset \mathbb{R}^n$, one has that $\min_{H \in G(n -1)}\lambda(K \mid H) \leq \max_{H \in G(n -1)}\lambda(K \cap H)?$
What I have done so far:
The case $n = 2$ is not too difficult to work out (True): Let $H_M \in \{H \in G(n-1) : \lambda(K \cap H) = \max_{A \in G(n-1)} \lambda(K \cap A) \}$.
Claim: $\lambda(K \cap H_M) = \lambda(K \mid H_M)$. Indeed, if not then we would have $K \cap H_M \subsetneq K \mid H_M.$ Consider $\mathrm{bd}({K \mid H_M}) = \{a, -a\}$. Let $\pi$ be the orthogonal projection operator from $K$ onto $H_M$ and consider $\pi^{-1}$(a). Choose any element $b \in \pi^{-1}(a)$, then $-b \in \pi^{-1}(-a)$ and the line segment $\ell$ from $b$ and $-b$ lies in $K$ by convexity. Then $\lambda(K \cap H_M) < \lambda(K \cap \ell) \leq \lambda(K \cap \mathrm{span}(\ell)),$ a contradiction to the maximality of $H_M$. Claim shown.
Then $\min_{H \in G(n -1)}\lambda(K \mid H) \leq \lambda(K \mid H_M) = \lambda (K \cap H_M) = \max_{H \in G(n-1)} \lambda(K \cap H).$
Where I am at now:
For higher dimensions, this argument breaks down of course, but I still think the original statement might be true. After working on this problem for a little bit today I thought that maybe this problem is well known. I figured I would ask those who are more knowledgeable in the field just in case so I don't reinvent the wheel.
UPDATE: Thanks to fedja (see below), the question has a negative result in general.