Telegram RegisterThe public register of Telegram
Telegram profile photo for Зожник. Наука о ЗОЖ

Channel

Зожник. Наука о ЗОЖ

@zozhnik_ru

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

9,283subscribers

-71 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001111330630
TypeChannel
Username@zozhnik_ru
CreatedBetween 1 February 2017 and 30 November 2019 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live17 September 2026
Measurements held13
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/zozhnik_ru

Topic

Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 11 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

9,2839,3549,318.57 August 2026 — 9,354 subscribers7 August 2026 — 9,354 subscribers11 August 2026 — 9,339 subscribers14 August 2026 — 9,324 subscribers17 August 2026 — 9,320 subscribers20 August 2026 — 9,319 subscribers23 August 2026 — 9,316 subscribers26 August 2026 — 9,308 subscribers29 August 2026 — 9,301 subscribers5 September 2026 — 9,296 subscribers10 September 2026 — 9,298 subscribers13 September 2026 — 9,285 subscribers17 September 2026 — 9,283 subscribers7 August 202617 September 2026
13 measurements spanning 40 days, net -71. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 9,272–9,365 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Sept 2026, 08:209,283-2
13 Sept 2026, 18:159,285-13
10 Sept 2026, 05:559,298+2
5 Sept 2026, 08:379,296-5
29 Aug 2026, 19:449,301-7
26 Aug 2026, 15:479,308-8
23 Aug 2026, 20:559,316-3
20 Aug 2026, 10:529,319-1
17 Aug 2026, 15:279,320-4
14 Aug 2026, 18:249,324-15
11 Aug 2026, 02:269,339-15
7 Aug 2026, 23:349,354no change
7 Aug 2026, 23:169,354first reading

Engagement

30 posts held, back to 7 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 30 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
10.5%
avg views ÷ 9,283 subscribers
Avg views / post
974
5 posts measured
Reaction rate
3.51%
reactions ÷ views · ER floor
Posts in window
5
of 30 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 28 August 2026
Posts held30 (7 July 202628 August 2026)
Views total4,870
Reactions total171
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 07:51 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime
1m 18s
Average length
26s

Measured directly from 3 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no mark.

Reaction mix

1,043 reactions across 30 posts, in 12 distinct kinds. The most used accounts for 33.8% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
35333.8%
👍32030.7%
🔥22821.9%
❤‍🔥989.40%
111.05%
🤔100.959%
🕊60.575%
🤷‍♂60.575%
👌50.479%
👎30.288%
🤯20.192%
🥴10.096%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 30 of the 30 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,043 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 30 most recent posts we hold, published 7 July 2026 to 28 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

28 Aug 2026, 09:56 UTC698 views39 reactionsread 29 August 2026
Photo

«Сердцу отпущен лимит ударов, а спорт его тратит» - живучий миф. На деле всё как раз наоборот. Австралийские кардиологи посчитали: у тренированных пульс покоя ниже, и за сутки сердце делает примерно на 11 500 ударов меньше. Около 4,2 млн ударов «экономии» в год. ☝️ Тренировки не изнашивают сердце — они учат его работать эффективнее. @zozhnik_ru

13👍11🔥8❤‍🔥52

26 Aug 2026, 07:25 UTC952 views36 reactionsread 29 August 2026
Photo

Качество белка / цена белка в ккал Чем правее и выше - тем лучше @zozhnik_ru

👍1412🔥9❤‍🔥1

25 Aug 2026, 10:00 UTC≈1,060 views35 reactionsread 29 August 2026
Video

Геймификация тренировок На видео 2 забавных примера, на которые наткнулся. @zozhnik_ru

🔥21👍10❤‍🔥4

24 Aug 2026, 17:21 UTC≈1,160 views27 reactionsread 29 August 2026
Photo

КБЖУ → КБЖУК 🥬 Большое обновление по клетчатке Мы провели масштабную работу по внедрению тотального учета клетчатки во всех продуктах в приложении "Зоя". Как это работает 1. Обновили базу данных до свежей версии USDA, также данные по клетчатке имелись в базе Скурихина, добавили клетчатку из Open Food Facts. А по недостающим данным: прогнали 3-уровневую оценку клетчатки с помощью ИИ по всем почти 11.000 продуктов

13🔥9👍5

24 Aug 2026, 07:28 UTC≈1,000 views34 reactionsread 29 August 2026
Photo

☝️НОВОСТИ ЗОЖ-НАУКИ за неделю №10 (18-24 августа) ☕️ У любителей кофе — меньше жира и больше мышц при том же ИМТ: анализ 2 264 финнов 46 лет показал: чем больше кофе, тем ниже общий и висцеральный жир, выше мышечная масса. Это наблюдательное исследование: не исключено, что не кофе делает людей поджарыми, а поджарые люди пьют больше кофе. 🏃 3 минуты спринтов сделали с кровью то, чего не смогли 90 минут умеренной езд

👍1312🔥9

20 Aug 2026, 14:50 UTC≈1,570 views49 reactionsread 29 August 2026
Photo

Про индекс насыщения продуктов. Или что съесть, чтобы не хотеть есть В 1995 году Сюзанна Холт с коллегами провела изящный эксперимент: людям давали порции 38 разных продуктов — все ровно по 240 ккал — и 2 часа измеряли, насколько они сыты. Белый хлеб приняли за 100%, остальное сравнивали с ним. Результаты, собственно, в таблице на картинке ☝️ 👉Оригинал списка в pdf В чём фокус? Никакой магии в картошке нет — есть

25👍17🔥5🤔2

19 Aug 2026, 11:08 UTC≈1,550 views36 reactionsread 29 August 2026
Photo

👂Почему нельзя чистить серу в ушах Мы тут проводим ревизию статей в обновленном Зожнике. Будем освежать данными важные статьи: по 2-3 в неделю. Кому интересны подробности: "Ушная сера: нужно ли чистить уши и как удалять серные пробки" Кратко суть: Чистить уши ватными палочками (и другими палочками!) не нужно: слуховой проход очищается самостоятельно, а палочки заталкивают серу вглубь и повышают риск серных пробок,

🔥16👍8🤔75

17 Aug 2026, 12:14 UTC≈1,610 views49 reactionsread 29 August 2026
Photo

☝️НОВОСТИ ЗОЖ-НАУКИ за неделю №9 (10–17 августа) 🦠 Когда в рационе мало клетчатки, кишечные бактерии переключаются на «поедание» защитного слизистого слоя кишечника — исследование на мышах показало, что клетчатка удерживает микробиом от разрушения муцинового барьера, а заодно нашло недооценённого игрока: устойчивые к перевариванию растительные белки, которые доходят до микробов толстой кишки и сдвигают их метаболиты

👍2111❤‍🔥11🔥6

14 Aug 2026, 11:15 UTC≈1,560 views20 reactionsread 29 August 2026
File

Что читают женщины, а что - мужчины? Диаграмма жанров книг по доле мужских / женских отзывов на Goodreads на основе анализа отзывов по 200.000 книг. Сверху: преобладание мужских отзывов, чем ниже чем больше доля женских. Шкала по горизонтали: соотношение м/ж #инфографика_по_пятницам

9👍7🤷‍♂4

13 Aug 2026, 11:28 UTC≈1,610 views35 reactionsread 29 August 2026
Photo

🤷‍♂️ Статистика обращений «на ТЫ» / «на ВЫ» *В американских приложениях о таком, конечно, не думают. Мы тут изначально решили взять на себя доп.обязательства и добавить в Зое обработку обращения к пользователю на его выбор «на Ты» или «на Вы». То есть можно указать имя как «Максим Сергеевич» и «на ВЫ» и Зоя перестанет «тыкать» в интерфейсе и отчетах. В общем, пусть ИИ будет максимально уважителен :) 😎Уверен, что

👍1811👌4🤯2

12 Aug 2026, 13:52 UTC≈1,780 views68 reactionsread 29 August 2026
Photo

Мы тут перезапускаем сайт Zozhnik.ru, чем на 14-й год существования открываем 3-й сезон нашей деятельности. В качестве заманухи полезных материалов (и особенно для профессионалов) добавили: Таблицу "Е-шек" - можно отфильтровать, что запрещено в ЕС и США, но разрешено в РФ. И наоборот. Таблицу САХЗАМЫ - аналогично Калькулятор % жира - тот, что установили в "Зое", с погрешностью всего 3-4%. Калькулятор 1ПМ (по 2 ф

🔥3620❤‍🔥10👍2

10 Aug 2026, 09:26 UTC≈1,960 views50 reactionsread 29 August 2026
Photo

НОВОСТИ ЗОЖ-НАУКИ за неделю №8 🥛Жирная молочка оправдана? В клиническом исследовании 74 взрослых с лишним весом 3 порции цельножирных молочных продуктов в день не ухудшили вес, состав тела, холестерин и чувствительность к инсулину — а давление даже улучшилось. *Нюанс: исследование частично финансировалось молочной индустрией (Dairy Research Cluster). 🍷Вид алкоголя имеет значение. В когорте UK Biobank (340 924 челов

21👍15🔥10❤‍🔥4

Showing the 12 most recent of 30 posts we hold for @zozhnik_ru. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Forward network

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Злой доктор Филатов
@doc_Filatov · 28,121
Telegram ranks this channel #18 of 86 here — alongside 85 others — read 10 September 2026
Павел Баранов. Эндокринология/диетология.
@pavelbaranov_md · 31,179
Telegram ranks this channel #34 of 96 here — alongside 95 others — read 6 September 2026
Рецепты Лайфхакера
@lh_eda · 38,747
Telegram ranks this channel #38 of 93 here — alongside 92 others — read 31 August 2026
Мудрость Фитнеса (тренер Кабуров)
@fitness_mayatnik · 25,728
Telegram ranks this channel #39 of 93 here — alongside 92 others — read 13 September 2026
Йод | Лайфхакер
@lh_health · 22,821
Telegram ranks this channel #40 of 95 here — alongside 94 others — read 19 September 2026

This channel appears in 5 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 17 September 2026 — this entry's latest reading, not the date you are reading this.

“Зожник. Наука о ЗОЖ” (@zozhnik_ru), 9,283 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/zozhnik_ru.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.