腦健康 ExposomeBrain-Health Exposome 檢測Check-in
輸入你的居住史與基本資料，看看累積的環境暴露（exposome）對應到多少「相對腦齡加速」年數。純前端計算，資料不上傳。Enter your residence history and basic profile to see how your accumulated exposome maps to a 'relative brain-aging' figure. Runs entirely in your browser — nothing is uploaded.
這個工具的起點，是我參與 2026 年阿茲海默症協會國際年會（AAIC）聽的其中一場演講主題：「為什麼每個人大腦老化的速度不一樣？」失智症的大腦病變往往在發病前 15–20 年就悄悄開始，而有些推動病變的因子就在生活中。講者分享的案例讓全場震撼，好幾位不到 60 歲、高學歷、沒有慢性病、生活型態健康的人卻確診阿茲海默症，而他們的共同點是長期住在空污嚴重的地區，腦影像顯示他們的大腦比實際年齡老了 15–25 歲。學者提出的論點是，這些環境中的危險因子推動著他們的大腦老化與病變。This tool began with one of the talks I attended at the 2026 Alzheimer's Association International Conference (AAIC): “Why do our brains age at different speeds?” Dementia's brain changes often begin quietly 15–20 years before symptoms — and some of the factors driving them are woven into everyday life. The cases the speaker shared stunned the room: several people under 60, highly educated, with no chronic disease and healthy lifestyles, yet diagnosed with Alzheimer's — their common thread was living long-term in heavily polluted areas, with brain scans showing brains 15–25 years older than their actual age. The researchers' argument was that these environmental risk factors were driving their brain aging and pathology.
這場演講後，我認為「及早覺察危險因子」，是讓所有人能立刻採取行動預防失智症的基礎。所以，我把可用的證據彙整成一個可計算的模型：以《Lancet》失智症委員會的可調整危險因子、公開的 PM2.5 衛星資料，以及「風險大約每 5–6 年翻倍」等文獻為基礎，再逐步接上 GBD、NCD-RisC、WHO、World Bank 等公開資料庫，讓不同國家也能互相比較。After that talk, I came to see noticing risk factors early as the foundation that lets anyone act right away to help prevent dementia. So I gathered the available evidence into a computable model — built on the Lancet Commission's modifiable risk factors, open satellite PM2.5 data, and findings such as risk roughly doubling every 5–6 years — then progressively wired in public databases (GBD, NCD-RisC, WHO, World Bank) so different countries can be compared.
使用者可以輸入歷年居住地與基本資料，看看自己累積的「exposome（環境暴露總和）」對應到多少『相對腦齡加速』年數；也能在全球地圖上瀏覽各國的失智盛行、空污、高齡化與可調控風險概況。它不是診斷、不是醫療器材，也不預測任何個人是否會失智——只希望讓我們對身邊這些「可以及早行動」的危險因子更有覺知。You can enter your residence history and basic profile to see how your accumulated 'exposome' maps to a 'relative brain-aging' figure in years — and browse each country's dementia prevalence, air pollution, aging and modifiable-risk picture on the global map. It is not a diagnosis, not a medical device, and predicts nothing about any individual — it exists only to raise awareness of the risk factors around us that we can act on early.
所有計算都在你的瀏覽器內完成，資料不會上傳或儲存到任何伺服器。All calculations run entirely in your browser — nothing is uploaded or stored on any server.
為了少填一步，第一段居住地的「國家」會依你目前的網路所在地或瀏覽器語系自動預設（不經第三方、不會索取定位權限），你可以隨時自行更改。To save a step, the first residence's country is pre-filled from your current network location or browser locale (no third party, no location-permission prompt); you can change it anytime.
本工具僅供一般健康教育與自我覺察之用，並非醫療器材、不是診斷或篩檢工具，無法預測任何人是否會罹患失智症。This tool is for general health education and self-awareness only. It is not a medical device, not a diagnostic or screening test, and cannot predict whether anyone will develop dementia.
- 結果描述的是「族群層級」的關聯（來自已發表研究），而不是對「你個人」的預測；同樣的因子，每個人的結果差異其實很大。Results describe population-level associations (from published research), not a prediction about you personally — individual outcomes vary a great deal.
- 這裡的「腦齡加速」是一個教育性的比喻數字，不是用腦部影像（MRI／EEG）量出來的真實腦齡。The 'brain-age acceleration' here is an educational illustration, not a real brain age measured from imaging (MRI/EEG).
- 本工具不能取代醫療專業判斷。如有任何健康疑慮，請諮詢合格的醫療人員。This does not replace professional medical advice. Consult a qualified healthcare provider for any health concern.
- PM2.5 採用 ACAG 衛星推估的逐年（1998–2024）縣市資料（1998 年以前的居住年份沿用 1998 值）。地圖上的失智盛行率為縣市層級的模型估計值，非實測。PM2.5 uses ACAG satellite-derived annual (1998–2024) county data (residence years before 1998 reuse the 1998 value). The dementia prevalence on the map is a county-level modelled estimate, not measured.
個人 14 項可調整失智症風險因子填寫Enter your 14 modifiable dementia risk factors
- 1基本資料About you
- 2居住史Places
- 3心血管代謝Cardiometabolic
- 4感官・心理Senses & mood
- 5生活型態Lifestyle
- 6結果Results
1. 關於你About you
2. 你住過的地方Places you've lived
加入你人生各階段主要居住的縣市與大約年份。系統會用該地區的年均 PM2.5 估算你「時間加權」的長期空氣污染暴露。年份可粗估即可。Add the main counties you've lived in across life, with rough years. We estimate your time-weighted long-term PM2.5 exposure from each area's annual mean. Approximate years are fine.
| 國家Country | 地區Region | 從From | 到To | PM2.5 |
|---|
⠿ 可上下拖曳調整居住順序（年份區間留在原位，只換地點）。⠿ Drag rows to reorder where you lived (the time slots stay put — only the places move).
3. 心血管與代謝Heart & metabolic
不確定就選「不確定」，不會被算成風險。這些對應到 Lancet 委員會可調整的失智風險因子。Pick 'Not sure' if you don't know — it won't be counted as a risk. These map to the Lancet Commission's modifiable dementia risk factors.
❤️ 心血管代謝❤️ Cardiometabolic
4. 感官・心理・社交Senses, mood & social
不確定就選「不確定」，不會被算成風險。Pick 'Not sure' if you don't know — it won't be counted as a risk.
👂 感官👂 Sensory
🧠 心理健康🧠 Mental health
🤝 社會與認知🤝 Social & cognitive
5. 生活型態與外傷Lifestyle & injury
最後幾題，填完就能看結果。Last few questions — then you'll see your results.
🚬 生活型態與外傷🚬 Lifestyle & injury
6. 你的結果Your results
各面向風險換算腦齡老化概況Brain-aging by domain (risk-converted)
你的風險因子：說明與建議Your flagged factors: what they mean & what to do
相對風險與腦齡計算方式How relative risk & brain age are calculated
每個「有」的因子會帶入已發表的相對風險（RR，主要來自 2024 年 Lancet 委員會與其引用的統合分析）。因為這些因子彼此相關、會重複計算，我們在合併時乘上一個縮減係數 λ = 0.6（近似委員會的 communality 調整），並設上限，避免高估。合併後的有效 RR 再換算成「腦齡加速」年數：Δ年 ≈ log₂(RR) × 5.5（失智風險大約每 5–6 年翻倍）。空氣污染以連續劑量處理（每 +5 µg/m³ 約 HR 1.08），因此不再重複計入委員會的類別式空污因子。Each 'yes' factor contributes a published relative risk (RR, mainly from the 2024 Lancet Commission and the meta-analyses it cites). Because these factors are correlated and would double-count, we combine them with a shrinkage factor λ = 0.6 (approximating the Commission's communality adjustment) and cap the total to avoid overstating. The combined effective RR is converted to 'brain-age acceleration' years: Δyears ≈ log₂(RR) × 5.5 (dementia risk roughly doubles every 5–6 years). PM2.5 is handled continuously (≈ HR 1.08 per +5 µg/m³), so the Commission's categorical air-pollution factor is not added on top.
假設與限制：λ = 0.6 與腦齡年數上限是本工具為避免高估所設的參數（非已發表常數）；PM2.5 採 ACAG 衛星年均資料（依居住縣市／國家與年份對應），歷史不足年份以最接近年份外推。這是教育性估計，非個人預測。Assumptions: λ = 0.6 and the brain-age cap are this tool's parameters to avoid overstatement (not published constants); PM2.5 uses ACAG satellite annual data (matched to your county/country and year), with missing historical years extrapolated from the nearest available year. This is an educational estimate, not a personal prediction.
全球地圖：高齡化、認知退化與危險因子概況Global map: aging, cognitive decline & risk factors
預設是「🌍 全球總覽」地球儀——每個國家以近年 PM2.5 或可調控失智風險（PAF，可歸因比例／population attributable fraction）著色，色階以 WHO 標準（≤5 µg/m³）為基準、可跨國比較。點任一國（或用選單切換到 20 多國）即可下鑽到該國各行政區的細節地圖，看更細的 PM2.5 與失智盛行「模型估計值」。把游標移到區域上看數值。The default is a 🌍 global overview globe — each country shaded by recent PM2.5 or modifiable dementia risk (PAF, population attributable fraction), on a WHO-anchored scale (≤5 µg/m³) comparable across countries. Click a country (or pick one of 20+ from the dropdown) to drill into its admin-1 detail map, with finer PM2.5 and MODELLED dementia-prevalence estimates. Hover a district for values.
※ 台灣失智盛行率為鄉鎮市區層級「65 歲以上盛行率」的模型估計（NHRI 年齡別盛行率 × 內政部 #77132 各區單一年齡人口，見下方說明表），非實測。PM2.5 為 ACAG 衛星資料（V6.GL.03）；台灣以外為各行政區（Natural Earth 界線）的衛星網格平均值。美國為本土 48 州＋DC（不含阿拉斯加／夏威夷）。※ Taiwan dementia prevalence is a township-level modelled estimate of prevalence among residents aged 65+ (NHRI age-band rates × MOI #77132 single-year-age population per township — see the method table below), not measured. PM2.5 is ACAG satellite data (V6.GL.03); outside Taiwan, values are grid means per admin-1 unit (Natural Earth boundaries). USA shows the contiguous 48 states + DC (Alaska/Hawaii excluded).
資料齊全度與來源Data coverage & sources
逐一揭露本工具各類資料的齊全度與出處：切換上方資料類型，表列各國的國家級／省縣級資料來源與年份。狀態：✅ 已用於工具・◐ 部分（種子估計）・○ 已找到來源待接入・— 尚無資料。皆為模型估計／最新可得估計，會持續補齊。Full disclosure of each data layer's coverage and provenance: pick a data type; the table lists every country's national / sub-national source and year. Status: ✅ in the tool · ◐ partial (seed) · ○ source identified, not yet wired · — none yet. All modelled / latest-available estimates; being filled in over time.
175 個國家/地區
各國省縣級高齡化數據（65 歲以上人口占比）Sub-national population aged 65+, by country
地圖上的每一個省縣級數字，在這裡以文字列出，每筆都標明來源與年份。展開「完整列表」可看該國全部行政區。Every sub-national figure on the map, listed as text with its source and year. Expand “Full list” for all units in a country.
土耳其 (81)
土耳其 65 歲以上人口占比最高的一級行政區是 Sinop（20.8%），最低是 Sirnak（3.7%）；全國未加權平均 12.2%（TÜİK ADNKS 2024 — population by province, single age & sex (press 53783)，2024 年）。In 土耳其, the admin-1 unit with the highest share of population aged 65+ is Sinop at 20.8%, and the lowest is Sirnak at 3.7%; the unweighted national figure is 12.2% (TÜİK ADNKS 2024 — population by province, single age & sex (press 53783), 2024).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Sinop | 20.8% |
| Kastamonu | 20.2% |
| Giresun | 19.1% |
| Artvin | 18.6% |
| Çankiri | 17.7% |
完整列表Full list (81)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Sinop | 20.8% |
| Kastamonu | 20.2% |
| Giresun | 19.1% |
| Artvin | 18.6% |
| Çankiri | 17.7% |
| Balikesir | 17.5% |
| Çanakkale | 17.2% |
| Çorum | 17.2% |
| Edirne | 17.2% |
| Tunceli | 17% |
| Burdur | 16.9% |
| Ordu | 16.5% |
| Bartın | 16.5% |
| Amasya | 16.4% |
| Kirklareli | 16.3% |
| Tokat | 15.9% |
| Zinguldak | 15.8% |
| Aydin | 15.6% |
| Gümüshane | 15.4% |
| Yozgat | 15.4% |
| Karabük | 15.3% |
| Bolu | 15.1% |
| Kütahya | 15.1% |
| Isparta | 15% |
| Rize | 15% |
| Ardahan | 14.9% |
| Trabzon | 14.8% |
| Sivas | 14.5% |
| Kirsehir | 14.3% |
| Mugla | 14.2% |
| Usak | 14.2% |
| Kinkkale | 14% |
| Erzincan | 13.9% |
| Samsun | 13.7% |
| Yalova | 13.6% |
| Izmir | 13.3% |
| Manisa | 13.2% |
| Eskisehir | 13.1% |
| Nevsehir | 13.1% |
| Bilecik | 13% |
| Denizli | 12.8% |
| Bayburt | 12.7% |
| Afyonkarahisar | 12.6% |
| Karaman | 12.2% |
| Malatya | 12.1% |
| Düzce | 11.9% |
| Elazig | 11.5% |
| Nigde | 11.4% |
| Sakarya | 11.3% |
| Mersin | 10.9% |
| Bursa | 10.8% |
| Konya | 10.8% |
| Aksaray | 10.6% |
| Ankara | 10.4% |
| Kayseri | 10.4% |
| Tekirdag | 10.2% |
| Antalya | 10.1% |
| Adana | 10% |
| Erzurum | 10% |
| Osmaniye | 10% |
| Kars | 9.6% |
| K. Maras | 9.6% |
| Adiyaman | 8.9% |
| Hatay | 8.9% |
| Kocaeli | 8.6% |
| Bingöl | 8.4% |
| Istanbul | 8.3% |
| Kilis | 8.1% |
| Iğdir | 7.9% |
| Mus | 6.2% |
| Bitlis | 6.1% |
| Gaziantep | 6.1% |
| Mardin | 6% |
| Agri | 5.8% |
| Siirt | 5.8% |
| Diyarbakir | 5.5% |
| Van | 5.1% |
| Batman | 5% |
| Sanliurfa | 4.4% |
| Hakkari | 4.3% |
| Sirnak | 3.7% |
來源：TÜİK ADNKS 2024 — population by province, single age & sex (press 53783)（2024 年）Source: TÜİK ADNKS 2024 — population by province, single age & sex (press 53783) (2024)
中國 (31)
中國 65 歲以上人口占比最高的一級行政區是 遼寧（17.42%），最低是 西藏自治區（5.67%）；全國未加權平均 13%（China 2020 Seventh National Population Census (provincial communiqués / NBS)，2020 年）。In 中國, the admin-1 unit with the highest share of population aged 65+ is Liaoning at 17.42%, and the lowest is Xizang at 5.67%; the unweighted national figure is 13% (China 2020 Seventh National Population Census (provincial communiqués / NBS), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 遼寧Liaoning | 17.42% |
| 重慶Chongqing | 17.08% |
| 四川Sichuan | 16.93% |
| 上海Shanghai | 16.28% |
| 江蘇Jiangsu | 16.2% |
完整列表Full list (31)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 遼寧Liaoning | 17.42% |
| 重慶Chongqing | 17.08% |
| 四川Sichuan | 16.93% |
| 上海Shanghai | 16.28% |
| 江蘇Jiangsu | 16.2% |
| 吉林Jilin | 15.61% |
| 黑龙江省Heilongjiang | 15.61% |
| 山東Shandong | 15.13% |
| 安徽Anhui | 15.01% |
| 湖南Hunan | 14.81% |
| 天津Tianjin | 14.75% |
| 湖北Hubei | 14.59% |
| 河北Hebei | 13.92% |
| 河南Henan | 13.49% |
| 陝西Shaanxi | 13.32% |
| 北京Beijing | 13.3% |
| 浙江Zhejiang | 13.27% |
| 內蒙古自治區Inner Mongol | 13.05% |
| 山西Shanxi | 12.9% |
| 甘肅Gansu | 12.58% |
| 廣西壯族自治區Guangxi | 12.2% |
| 江西Jiangxi | 11.89% |
| 貴州Guizhou | 11.56% |
| 福建Fujian | 11.1% |
| 雲南Yunnan | 10.75% |
| 海南Hainan | 10.43% |
| 寧夏回族自治區Ningxia | 9.62% |
| Qinghai | 8.68% |
| 廣東Guangdong | 8.58% |
| 新疆維吾爾自治區Xinjiang | 7.76% |
| 西藏自治區Xizang | 5.67% |
來源：China 2020 Seventh National Population Census (provincial communiqués / NBS)（2020 年）Source: China 2020 Seventh National Population Census (provincial communiqués / NBS) (2020)
巴西 (27)
巴西 65 歲以上人口占比最高的一級行政區是 Rio Grande do Sul（14.1%），最低是 Roraima（5.1%）；全國未加權平均 9.5%（IBGE Censo 2022 (SIDRA 9514)，2022 年）。In 巴西, the admin-1 unit with the highest share of population aged 65+ is Rio Grande do Sul at 14.1%, and the lowest is Roraima at 5.1%; the unweighted national figure is 9.5% (IBGE Censo 2022 (SIDRA 9514), 2022).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Rio Grande do Sul | 14.1% |
| Rio de Janeiro | 13.1% |
| Minas Gerais | 12.4% |
| São Paulo | 11.9% |
| Paraná | 11.3% |
完整列表Full list (27)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Rio Grande do Sul | 14.1% |
| Rio de Janeiro | 13.1% |
| Minas Gerais | 12.4% |
| São Paulo | 11.9% |
| Paraná | 11.3% |
| Espírito Santo | 11.2% |
| Paraíba | 11% |
| Piauí | 10.7% |
| Bahia | 10.6% |
| Rio Grande do Norte | 10.5% |
| Ceará | 10.4% |
| Santa Catarina | 10.4% |
| Pernambuco | 10.2% |
| Mato Grosso do Sul | 9.6% |
| Sergipe | 9.2% |
| Goiás | 9.2% |
| Alagoas | 8.9% |
| Distrito Federal | 8.8% |
| Tocantins | 8.6% |
| Maranhão | 8.4% |
| Rondônia | 8.1% |
| Mato Grosso | 7.7% |
| Pará | 7.2% |
| Acre | 6.3% |
| Amazonas | 5.9% |
| Amapá | 5.5% |
| Roraima | 5.1% |
來源：IBGE Censo 2022 (SIDRA 9514)（2022 年）Source: IBGE Censo 2022 (SIDRA 9514) (2022)
日本 (47)
日本 65 歲以上人口占比最高的一級行政區是 秋田県（37.6%），最低是 沖縄県（22.6%）；全國未加權平均 30.9%（Japan 2020 Census via e-Stat (0003448299, 年齢別割合)，2020 年）。In 日本, the admin-1 unit with the highest share of population aged 65+ is Akita at 37.6%, and the lowest is Okinawa at 22.6%; the unweighted national figure is 30.9% (Japan 2020 Census via e-Stat (0003448299, 年齢別割合), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 秋田県Akita | 37.6% |
| 高知県Kōchi | 35.6% |
| 山口県Yamaguchi | 34.8% |
| 徳島県Tokushima | 34.5% |
| 島根県Shimane | 34.4% |
完整列表Full list (47)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 秋田県Akita | 37.6% |
| 高知県Kōchi | 35.6% |
| 山口県Yamaguchi | 34.8% |
| 徳島県Tokushima | 34.5% |
| 島根県Shimane | 34.4% |
| 山形県Yamagata | 34% |
| 青森県Aomori | 33.9% |
| 岩手県Iwate | 33.8% |
| 大分県Ōita | 33.5% |
| 和歌山県Wakayama | 33.4% |
| 愛媛県Ehime | 33.4% |
| 長崎県Nagasaki | 33.1% |
| 新潟県Niigata | 32.9% |
| 富山県Toyama | 32.8% |
| 鹿児島県Kagoshima | 32.8% |
| 宮崎県Miyazaki | 32.7% |
| 鳥取県Tottori | 32.5% |
| 北海道Hokkaidō | 32.2% |
| 長野県Nagano | 32.2% |
| 香川県Kagawa | 31.9% |
| 福島県Fukushima | 31.8% |
| 奈良県Nara | 31.7% |
| 熊本県Kumamoto | 31.6% |
| 山梨県Yamanashi | 31.1% |
| 福井県Fukui | 30.8% |
| 佐賀県Saga | 30.8% |
| 岡山県Okayama | 30.7% |
| 岐阜県Gifu | 30.6% |
| 群馬県Gunma | 30.4% |
| Shizuoka | 30.2% |
| 三重県Mie | 30.2% |
| 石川県Ishikawa | 30% |
| 茨城県Ibaraki | 29.9% |
| 広島県Hiroshima | 29.6% |
| 京都府Kyōto | 29.4% |
| 兵庫県Hyōgo | 29.3% |
| 栃木県Tochigi | 29.2% |
| 宮城県Miyagi | 28.3% |
| 福岡県Fukuoka | 28.1% |
| 千葉県Chiba | 27.6% |
| 大阪府Ōsaka | 27.5% |
| 埼玉県Saitama | 27.1% |
| 滋賀県Shiga | 26.4% |
| 神奈川県Kanagawa | 25.6% |
| 愛知県Aichi | 25.4% |
| 東京都Tokyo | 22.8% |
| 沖縄県Okinawa | 22.6% |
來源：Japan 2020 Census via e-Stat (0003448299, 年齢別割合)（2020 年）Source: Japan 2020 Census via e-Stat (0003448299, 年齢別割合) (2020)
加拿大 (13)
加拿大 65 歲以上人口占比最高的一級行政區是 Newfoundland and Labrador（25.2%），最低是 Nunavut（5.2%）；全國未加權平均 18.1%（Statistics Canada, table 17-10-0005，2025 年）。In 加拿大, the admin-1 unit with the highest share of population aged 65+ is Newfoundland and Labrador at 25.2%, and the lowest is Nunavut at 5.2%; the unweighted national figure is 18.1% (Statistics Canada, table 17-10-0005, 2025).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Newfoundland and Labrador | 25.2% |
| New Brunswick | 23.3% |
| Nova Scotia | 22.6% |
| Québec | 21.7% |
| Prince Edward Island | 20.9% |
完整列表Full list (13)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Newfoundland and Labrador | 25.2% |
| New Brunswick | 23.3% |
| Nova Scotia | 22.6% |
| Québec | 21.7% |
| Prince Edward Island | 20.9% |
| British Columbia | 20.5% |
| Ontario | 18.9% |
| Saskatchewan | 17.8% |
| Manitoba | 17.2% |
| Alberta | 15.5% |
| Yukon | 15.3% |
| Northwest Territories | 11.5% |
| Nunavut | 5.2% |
來源：Statistics Canada, table 17-10-0005（2025 年）Source: Statistics Canada, table 17-10-0005 (2025)
台灣 (370)
台灣 65 歲以上人口占比最高的鄉鎮市區是 新北市平溪區（28.6%），最低是 高雄市那瑪夏區（7.1%）；全國未加權平均 16%（MOI 內政部戶政司 #77132 (village single-year age, 107/03)，2018 年）。In 台灣, the township with the highest share of population aged 65+ is Pingxi District, New Taipei City at 28.6%, and the lowest is Namaxia District, Kaohsiung City at 7.1%; the unweighted national figure is 16% (MOI 內政部戶政司 #77132 (village single-year age, 107/03), 2018).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 新北市平溪區Pingxi District, New Taipei City | 28.6% |
| 高雄市田寮區Tianliao District, Kaohsiung City | 27.8% |
| 台南市左鎮區Zuozhen District, Tainan City | 27.4% |
| 苗栗縣獅潭鄉Shitan Township, Miaoli County | 26.5% |
| 台南市龍崎區Longqi District, Tainan City | 26% |
完整列表Full list (370)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 新北市平溪區Pingxi District, New Taipei City | 28.6% |
| 高雄市田寮區Tianliao District, Kaohsiung City | 27.8% |
| 台南市左鎮區Zuozhen District, Tainan City | 27.4% |
| 苗栗縣獅潭鄉Shitan Township, Miaoli County | 26.5% |
| 台南市龍崎區Longqi District, Tainan City | 26% |
| 新竹縣峨眉鄉Emei Township, Hsinchu County | 25.8% |
| 嘉義縣六腳鄉Liujiao Township, Chiayi County | 25.5% |
| 新北市雙溪區Shuangxi District, New Taipei City | 25.3% |
| 嘉義縣鹿草鄉Lucao Township, Chiayi County | 25% |
| 嘉義縣義竹鄉Yizhu Township, Chiayi County | 24.7% |
| 台南市後壁區Houbi District, Tainan City | 24.5% |
| 台南市大內區Danei District, Tainan City | 24.5% |
| 彰化縣大城鄉Dacheng Township, Changhua County | 24.4% |
| 雲林縣水林鄉Shuilin Township, Yunlin County | 24.4% |
| 高雄市美濃區Meinong District, Kaohsiung City | 24.4% |
| 花蓮縣鳳林鎮Fenglin Township, Hualien County | 24.3% |
| 新北市坪林區Pinglin District, New Taipei City | 24.2% |
| 台南市白河區Baihe District, Tainan City | 23.9% |
| 雲林縣元長鄉Yuanchang Township, Yunlin County | 23.7% |
| 台東縣長濱鄉Changbin Township, Taitung County | 23.5% |
| 苗栗縣西湖鄉Xihu Township, Miaoli County | 23.4% |
| 嘉義縣溪口鄉Xikou Township, Chiayi County | 23.4% |
| 台南市東山區Dongshan District, Tainan City | 23.1% |
| 屏東縣高樹鄉Gaoshu Township, Pingtung County | 22.9% |
| 嘉義縣東石鄉Dongshi Township, Chiayi County | 22.7% |
| 花蓮縣富里鄉Fuli Township, Hualien County | 22.7% |
| 彰化縣二水鄉Ershui Township, Changhua County | 22.3% |
| 嘉義縣梅山鄉Meishan Township, Chiayi County | 22.2% |
| 台南市楠西區Nanxi District, Tainan City | 22.2% |
| 台南市南化區Nanhua District, Tainan City | 22.2% |
| 台東縣東河鄉Donghe Township, Taitung County | 22.1% |
| 高雄市杉林區Shanlin District, Kaohsiung City | 22.1% |
| 南投縣中寮鄉Zhongliao Township, Nantou County | 22% |
| 雲林縣東勢鄉Dongshi Township, Yunlin County | 22% |
| 雲林縣二崙鄉Erlun Township, Yunlin County | 21.9% |
| 雲林縣四湖鄉Sihu Township, Yunlin County | 21.8% |
| 高雄市前金區Qianjin District, Kaohsiung City | 21.8% |
| 花蓮縣光復鄉Guangfu Township, Hualien County | 21.7% |
| 彰化縣竹塘鄉Zhutang Township, Changhua County | 21.6% |
| 南投縣鹿谷鄉Lugu Township, Nantou County | 21.6% |
| 台南市玉井區Yujing District, Tainan City | 21.6% |
| 新竹縣橫山鄉Hengshan Township, Hsinchu County | 21.5% |
| 高雄市內門區Neimen District, Kaohsiung City | 21.3% |
| 彰化縣芳苑鄉Fangyuan Township, Changhua County | 21.2% |
| 高雄市鹽埕區Yancheng District, Kaohsiung City | 21.2% |
| 新北市貢寮區Gongliao District, New Taipei City | 21.2% |
| 苗栗縣三灣鄉Sanwan Township, Miaoli County | 21.1% |
| 南投縣集集鎮Jiji Township, Nantou County | 21.1% |
| 屏東縣車城鄉Checheng Township, Pingtung County | 21.1% |
| 台東縣池上鄉Chishang Township, Taitung County | 21% |
| 花蓮縣瑞穗鄉Ruisui Township, Hualien County | 21% |
| 高雄市六龜區Liugui District, Kaohsiung City | 21% |
| 台南市將軍區Jiangjun District, Tainan City | 20.8% |
| 花蓮縣豐濱鄉Fengbin Township, Hualien County | 20.7% |
| 南投縣魚池鄉Yuchi Township, Nantou County | 20.6% |
| 嘉義縣大林鎮Dalin Township, Chiayi County | 20.6% |
| 屏東縣南州鄉Nanzhou Township, Pingtung County | 20.6% |
| 新北市石碇區Shiding District, New Taipei City | 20.6% |
| 台南市山上區Shanshang District, Tainan City | 20.6% |
| 雲林縣古坑鄉Gukeng Township, Yunlin County | 20.5% |
| 雲林縣大埤鄉Dabi Township, Yunlin County | 20.5% |
| 雲林縣崙背鄉Lunbei Township, Yunlin County | 20.5% |
| 屏東縣佳冬鄉Jiadong Township, Pingtung County | 20.5% |
| 高雄市新興區Xinxing District, Kaohsiung City | 20.5% |
| 高雄市旗山區Qishan District, Kaohsiung City | 20.5% |
| 台南市下營區Xiaying District, Tainan City | 20.5% |
| 南投縣水里鄉Shuili Township, Nantou County | 20.4% |
| 屏東縣新埤鄉Xinpi Township, Pingtung County | 20.4% |
| 澎湖縣西嶼鄉Xiyu Township, Penghu County | 20.4% |
| 新竹縣關西鎮Guanxi Township, Hsinchu County | 20.3% |
| 新竹縣北埔鄉Beipu Township, Hsinchu County | 20.3% |
| 苗栗縣大湖鄉Dahu Township, Miaoli County | 20.3% |
| 苗栗縣南庄鄉Nanzhuang Township, Miaoli County | 20.2% |
| 台南市柳營區Liuying District, Tainan City | 20.2% |
| 嘉義縣新港鄉Xingang Township, Chiayi County | 20.1% |
| 64000051 （來源代碼，地名未確認）(source code; name unverified) | 20.1% |
| 高雄市甲仙區Jiaxian District, Kaohsiung City | 20% |
| 苗栗縣卓蘭鎮Zhuolan Township, Miaoli County | 19.9% |
| 嘉義縣布袋鎮Budai Township, Chiayi County | 19.9% |
| 台東縣鹿野鄉Luye Township, Taitung County | 19.9% |
| 花蓮縣玉里鎮Yuli Township, Hualien County | 19.9% |
| 南投縣國姓鄉Guoxing Township, Nantou County | 19.8% |
| 雲林縣褒忠鄉Baozhong Township, Yunlin County | 19.8% |
| 屏東縣林邊鄉Linbian Township, Pingtung County | 19.8% |
| 台南市七股區Qigu District, Tainan City | 19.8% |
| 屏東縣竹田鄉Zhutian Township, Pingtung County | 19.7% |
| 台北市大安區Da'an District, Taipei City | 19.4% |
| 雲林縣臺西鄉Taixi Township, Yunlin County | 19.3% |
| 台東縣成功鎮Chenggong Township, Taitung County | 19.3% |
| 台南市鹽水區Yanshui District, Tainan City | 19.3% |
| 苗栗縣通霄鎮Tongxiao Township, Miaoli County | 19.2% |
| 彰化縣溪州鄉Xizhou Township, Changhua County | 19.1% |
| 雲林縣土庫鎮Tuku Township, Yunlin County | 19.1% |
| 台東縣關山鎮Guanshan Township, Taitung County | 19.1% |
| 澎湖縣望安鄉Wang'an Township, Penghu County | 19.1% |
| 宜蘭縣三星鄉Sanxing Township, Yilan County | 19% |
| 苗栗縣頭屋鄉Touwu Township, Miaoli County | 19% |
| 嘉義縣竹崎鄉Zhuqi Township, Chiayi County | 19% |
| 嘉義縣番路鄉Fanlu Township, Chiayi County | 19% |
| 花蓮縣壽豐鄉Shoufeng Township, Hualien County | 19% |
| 雲林縣口湖鄉Kouhu Township, Yunlin County | 18.9% |
| 屏東縣麟洛鄉Linluo Township, Pingtung County | 18.9% |
| 屏東縣萬巒鄉Wanluan Township, Pingtung County | 18.7% |
| 台中市東勢區Dongshi District, Taichung City | 18.7% |
| 雲林縣北港鎮Beigang Township, Yunlin County | 18.6% |
| 苗栗縣銅鑼鄉Tongluo Township, Miaoli County | 18.5% |
| 屏東縣枋寮鄉Fangliao Township, Pingtung County | 18.5% |
| 基隆市仁愛區Ren'ai District, Keelung City | 18.5% |
| 高雄市苓雅區Lingya District, Kaohsiung City | 18.5% |
| 新竹縣新埔鎮Xinpu Township, Hsinchu County | 18.4% |
| 台北市萬華區Wanhua District, Taipei City | 18.4% |
| 彰化縣二林鎮Erlin Township, Changhua County | 18.3% |
| 台中市新社區Xinshe District, Taichung City | 18.3% |
| 宜蘭縣蘇澳鎮Su'ao Township, Yilan County | 18.2% |
| 南投縣名間鄉Mingjian Township, Nantou County | 18.2% |
| 台南市麻豆區Madou District, Tainan City | 18.2% |
| 南投縣竹山鎮Zhushan Township, Nantou County | 18.1% |
| 雲林縣林內鄉Linnei Township, Yunlin County | 18.1% |
| 屏東縣枋山鄉Fangshan Township, Pingtung County | 18.1% |
| 台東縣太麻里鄉Taimali Township, Taitung County | 18.1% |
| 台北市松山區Songshan District, Taipei City | 18.1% |
| 台北市信義區Xinyi District, Taipei City | 18% |
| 彰化縣芬園鄉Fenyuan Township, Changhua County | 17.9% |
| 台南市北門區Beimen District, Tainan City | 17.9% |
| 台南市六甲區Liujia District, Tainan City | 17.8% |
| 嘉義縣朴子市Puzi City, Chiayi County | 17.7% |
| 彰化縣埤頭鄉Pitou Township, Changhua County | 17.6% |
| 雲林縣莿桐鄉Citong Township, Yunlin County | 17.6% |
| 澎湖縣白沙鄉Baisha Township, Penghu County | 17.6% |
| 台南市中西區West Central District, Tainan City | 17.6% |
| 苗栗縣後龍鎮Houlong Township, Miaoli County | 17.5% |
| 屏東縣滿州鄉Manzhou Township, Pingtung County | 17.5% |
| 彰化縣埔鹽鄉Puyan Township, Changhua County | 17.4% |
| 雲林縣西螺鎮Xiluo Township, Yunlin County | 17.4% |
| 澎湖縣湖西鄉Huxi Township, Penghu County | 17.4% |
| 苗栗縣造橋鄉Zaoqiao Township, Miaoli County | 17.3% |
| 彰化縣田中鎮Tianzhong Township, Changhua County | 17.3% |
| 屏東縣內埔鄉Neipu Township, Pingtung County | 17.3% |
| 台北市中山區Zhongshan District, Taipei City | 17.3% |
| 台北市中正區Zhongzheng District, Taipei City | 17.3% |
| 台中市中區Central District, Taichung City | 17.3% |
| 台南市關廟區Guanmiao District, Tainan City | 17.3% |
| 新北市萬里區Wanli District, New Taipei City | 17.2% |
| 台南市官田區Guantian District, Tainan City | 17.1% |
| 台南市學甲區Xuejia District, Tainan City | 17.1% |
| 新竹縣芎林鄉Qionglin Township, Hsinchu County | 17% |
| 新北市瑞芳區Ruifang District, New Taipei City | 17% |
| 台中市石岡區Shigang District, Taichung City | 17% |
| 宜蘭縣礁溪鄉Jiaoxi Township, Yilan County | 16.9% |
| 台北市大同區Datong District, Taipei City | 16.9% |
| 台北市士林區Shilin District, Taipei City | 16.9% |
| 宜蘭縣頭城鎮Toucheng Township, Yilan County | 16.8% |
| 雲林縣斗南鎮Dounan Township, Yunlin County | 16.8% |
| 基隆市中正區Zhongzheng District, Keelung City | 16.8% |
| 新北市永和區Yonghe District, New Taipei City | 16.8% |
| 台東縣卑南鄉Beinan Township, Taitung County | 16.6% |
| 澎湖縣七美鄉Qimei Township, Penghu County | 16.5% |
| 嘉義縣水上鄉Shuishang Township, Chiayi County | 16.4% |
| 嘉義縣中埔鄉Zhongpu Township, Chiayi County | 16.4% |
| 屏東縣里港鄉Ligang Township, Pingtung County | 16.4% |
| 新北市三芝區Sanzhi District, New Taipei City | 16.4% |
| 台中市大安區Da'an District, Taichung City | 16.4% |
| 苗栗縣公館鄉Gongguan Township, Miaoli County | 16.3% |
| 高雄市燕巢區Yanchao District, Kaohsiung City | 16.3% |
| 台中市和平區Heping District, Taichung City | 16.3% |
| 桃園市新屋區Xinwu District, Taoyuan City | 16.3% |
| 苗栗縣苗栗市Miaoli City, Miaoli County | 16.2% |
| 南投縣埔里鎮Puli Township, Nantou County | 16.2% |
| 高雄市茄萣區Qieding District, Kaohsiung City | 16.2% |
| 新北市新店區Xindian District, New Taipei City | 16.2% |
| 台南市西港區Xigang District, Tainan City | 16.2% |
| 苗栗縣三義鄉Sanyi Township, Miaoli County | 16.1% |
| 屏東縣長治鄉Changzhi Township, Pingtung County | 16.1% |
| 屏東縣鹽埔鄉Yanpu Township, Pingtung County | 16.1% |
| 高雄市大樹區Dashu District, Kaohsiung City | 16.1% |
| 宜蘭縣壯圍鄉Zhuangwei Township, Yilan County | 16% |
| 彰化縣田尾鄉Tianwei Township, Changhua County | 16% |
| 屏東縣新園鄉Xinyuan Township, Pingtung County | 16% |
| 宜蘭縣員山鄉Yuanshan Township, Yilan County | 15.9% |
| 高雄市橋頭區Qiaotou District, Kaohsiung City | 15.9% |
| 新北市石門區Shimen District, New Taipei City | 15.9% |
| 台南市新化區Xinhua District, Tainan City | 15.9% |
| 嘉義縣大埔鄉Dapu Township, Chiayi County | 15.8% |
| 高雄市前鎮區Qianzhen District, Kaohsiung City | 15.8% |
| 基隆市中山區Zhongshan District, Keelung City | 15.7% |
| 台北市北投區Beitou District, Taipei City | 15.7% |
| 台南市南區South District, Tainan City | 15.7% |
| 宜蘭縣五結鄉Wujie Township, Yilan County | 15.5% |
| 苗栗縣苑裡鎮Yuanli Township, Miaoli County | 15.5% |
| 高雄市彌陀區Mituo District, Kaohsiung City | 15.5% |
| 台南市新營區Xinying District, Tainan City | 15.5% |
| 南投縣南投市Nantou City, Nantou County | 15.4% |
| 宜蘭縣冬山鄉Dongshan Township, Yilan County | 15.3% |
| 屏東縣九如鄉Jiuru Township, Pingtung County | 15.2% |
| 基隆市信義區Xinyi District, Keelung City | 15.2% |
| 嘉義市東區East District, Chiayi City | 15.2% |
| 台南市佳里區Jiali District, Tainan City | 15.2% |
| 彰化縣北斗鎮Beidou Township, Changhua County | 15.1% |
| 屏東縣潮州鎮Chaozhou Township, Pingtung County | 15.1% |
| 屏東縣萬丹鄉Wandan Township, Pingtung County | 15.1% |
| 高雄市鳥松區Niaosong District, Kaohsiung City | 15.1% |
| 彰化縣永靖鄉Yongjing Township, Changhua County | 15% |
| 南投縣草屯鎮Caotun Township, Nantou County | 15% |
| 台北市文山區Wenshan District, Taipei City | 15% |
| 高雄市旗津區Qijin District, Kaohsiung City | 15% |
| 彰化縣社頭鄉Shetou Township, Changhua County | 14.9% |
| 雲林縣虎尾鎮Huwei Township, Yunlin County | 14.9% |
| 新北市金山區Jinshan District, New Taipei City | 14.9% |
| 屏東縣屏東市Pingtung City, Pingtung County | 14.8% |
| 新竹縣寶山鄉Baoshan Township, Hsinchu County | 14.7% |
| 屏東縣琉球鄉Liuqiu Township, Pingtung County | 14.7% |
| 高雄市阿蓮區Alian District, Kaohsiung City | 14.7% |
| 高雄市路竹區Luzhu District, Kaohsiung City | 14.7% |
| 嘉義縣民雄鄉Minxiong Township, Chiayi County | 14.6% |
| 台東縣大武鄉Dawu Township, Taitung County | 14.6% |
| 台北市南港區Nangang District, Taipei City | 14.6% |
| 新北市中和區Zhonghe District, New Taipei City | 14.6% |
| 台南市善化區Shanhua District, Tainan City | 14.6% |
| 高雄市湖內區Hunei District, Kaohsiung City | 14.5% |
| 宜蘭縣羅東鎮Luodong Township, Yilan County | 14.4% |
| 嘉義縣阿里山鄉Alishan Township, Chiayi County | 14.4% |
| 台東縣臺東市Taitung City, Taitung County | 14.4% |
| 宜蘭縣宜蘭市Yilan City, Yilan County | 14.3% |
| 花蓮縣花蓮市Hualien City, Hualien County | 14.3% |
| 台南市安定區Anding District, Tainan City | 14.3% |
| 台南市北區North District, Tainan City | 14.3% |
| 彰化縣埔心鄉Puxin Township, Changhua County | 14.2% |
| 屏東縣崁頂鄉Kanding Township, Pingtung County | 14.2% |
| 台中市西區West District, Taichung City | 14.2% |
| 台中市北區North District, Taichung City | 14.2% |
| 金門縣金沙鎮Jinsha Township, Kinmen County | 14.2% |
| 彰化縣彰化市Changhua City, Changhua County | 14.1% |
| 彰化縣福興鄉Fuxing Township, Changhua County | 14.1% |
| 屏東縣恆春鎮Hengchun Township, Pingtung County | 14.1% |
| 屏東縣霧臺鄉Wutai Township, Pingtung County | 14% |
| 基隆市七堵區Qidu District, Keelung City | 14% |
| 台中市東區East District, Taichung City | 14% |
| 金門縣烈嶼鄉Lieyu Township, Kinmen County | 14% |
| 彰化縣員林市Yuanlin City, Changhua County | 13.9% |
| 澎湖縣馬公市Magong City, Penghu County | 13.9% |
| 高雄市梓官區Ziguan District, Kaohsiung City | 13.9% |
| 台中市清水區Qingshui District, Taichung City | 13.8% |
| 台中市后里區Houli District, Taichung City | 13.8% |
| 台中市霧峰區Wufeng District, Taichung City | 13.8% |
| 花蓮縣吉安鄉Ji'an Township, Hualien County | 13.7% |
| 高雄市鼓山區Gushan District, Kaohsiung City | 13.7% |
| 高雄市岡山區Gangshan District, Kaohsiung City | 13.7% |
| 嘉義市西區West District, Chiayi City | 13.6% |
| 64000121 （來源代碼，地名未確認）(source code; name unverified) | 13.6% |
| 彰化縣線西鄉Xianxi Township, Changhua County | 13.5% |
| 雲林縣斗六市Douliu City, Yunlin County | 13.5% |
| 屏東縣東港鎮Donggang Township, Pingtung County | 13.5% |
| 花蓮縣新城鄉Xincheng Township, Hualien County | 13.5% |
| 新北市淡水區Tamsui District, New Taipei City | 13.5% |
| 彰化縣鹿港鎮Lukang Township, Changhua County | 13.4% |
| 彰化縣大村鄉Dacun Township, Changhua County | 13.4% |
| 基隆市安樂區Anle District, Keelung City | 13.4% |
| 彰化縣溪湖鎮Xihu Township, Changhua County | 13.3% |
| 新北市板橋區Banqiao District, New Taipei City | 13.3% |
| 新北市三重區Sanchong District, New Taipei City | 13.3% |
| 台南市仁德區Rende District, Tainan City | 13.3% |
| 苗栗縣泰安鄉Tai'an Township, Miaoli County | 13.2% |
| 彰化縣花壇鄉Huatan Township, Changhua County | 13.2% |
| 高雄市永安區Yong'an District, Kaohsiung City | 13.2% |
| 台中市外埔區Waipu District, Taichung City | 13.2% |
| 台南市東區East District, Tainan City | 13.2% |
| 新竹縣竹東鎮Zhudong Township, Hsinchu County | 13.1% |
| 高雄市大社區Dashe District, Kaohsiung City | 13.1% |
| 桃園市大溪區Daxi District, Taoyuan City | 13.1% |
| 嘉義縣太保市Taibao City, Chiayi County | 13% |
| 新北市深坑區Shenkeng District, New Taipei City | 13% |
| 台中市豐原區Fengyuan District, Taichung City | 13% |
| 台中市大甲區Dajia District, Taichung City | 13% |
| 連江縣北竿鄉Beigan Township, Lienchiang County | 13% |
| 高雄市林園區Linyuan District, Kaohsiung City | 12.9% |
| 高雄市大寮區Daliao District, Kaohsiung City | 12.9% |
| 連江縣莒光鄉Juguang Township, Lienchiang County | 12.9% |
| 彰化縣秀水鄉Xiushui Township, Changhua County | 12.8% |
| 屏東縣牡丹鄉Mudan Township, Pingtung County | 12.8% |
| 新竹市北區North District, Hsinchu City | 12.8% |
| 基隆市暖暖區Nuannuan District, Keelung City | 12.7% |
| 64000052 （來源代碼，地名未確認）(source code; name unverified) | 12.7% |
| 新北市烏來區Wulai District, New Taipei City | 12.6% |
| 新北市汐止區Xizhi District, New Taipei City | 12.5% |
| 台中市大肚區Dadu District, Taichung City | 12.5% |
| 金門縣金城鎮Jincheng Township, Kinmen County | 12.5% |
| 苗栗縣頭份市Toufen City, Miaoli County | 12.2% |
| 彰化縣和美鎮Hemei Township, Changhua County | 12.2% |
| 台中市神岡區Shengang District, Taichung City | 12.2% |
| 台南市新市區Xinshi District, Tainan City | 12.2% |
| 高雄市左營區Zuoying District, Kaohsiung City | 12.1% |
| 新竹縣湖口鄉Hukou Township, Hsinchu County | 12% |
| 彰化縣伸港鄉Shengang Township, Changhua County | 12% |
| 台南市歸仁區Guiren District, Tainan City | 12% |
| 桃園市龍潭區Longtan District, Taoyuan City | 12% |
| 桃園市觀音區Guanyin District, Taoyuan City | 12% |
| 台北市內湖區Neihu District, Taipei City | 11.9% |
| 金門縣金湖鎮Jinhu Township, Kinmen County | 11.9% |
| 64000122 （來源代碼，地名未確認）(source code; name unverified) | 11.8% |
| 台東縣達仁鄉Daren Township, Taitung County | 11.7% |
| 高雄市小港區Xiaogang District, Kaohsiung City | 11.7% |
| 桃園市復興區Fuxing District, Taoyuan City | 11.7% |
| 新北市八里區Bali District, New Taipei City | 11.6% |
| 台中市烏日區Wuri District, Taichung City | 11.6% |
| 高雄市楠梓區Nanzi District, Kaohsiung City | 11.4% |
| 苗栗縣竹南鎮Zhunan Township, Miaoli County | 11.3% |
| 雲林縣麥寮鄉Mailiao Township, Yunlin County | 11.3% |
| 桃園市中壢區Zhongli District, Taoyuan City | 11.2% |
| 南投縣信義鄉Xinyi Township, Nantou County | 11.1% |
| 新竹市東區East District, Hsinchu City | 11.1% |
| 新北市三峽區Sanxia District, New Taipei City | 11.1% |
| 屏東縣瑪家鄉Majia Township, Pingtung County | 11% |
| 屏東縣獅子鄉Shizi Township, Pingtung County | 11% |
| 新北市鶯歌區Yingge District, New Taipei City | 11% |
| 新竹市香山區Xiangshan District, Hsinchu City | 10.9% |
| 高雄市仁武區Renwu District, Kaohsiung City | 10.9% |
| 台中市梧棲區Wuqi District, Taichung City | 10.9% |
| 桃園市大園區Dayuan District, Taoyuan City | 10.9% |
| 金門縣金寧鄉Jinning Township, Kinmen County | 10.9% |
| 新竹縣五峰鄉Wufeng Township, Hsinchu County | 10.8% |
| 屏東縣春日鄉Chunri Township, Pingtung County | 10.8% |
| 台中市南區South District, Taichung City | 10.8% |
| 桃園市龜山區Guishan District, Taoyuan City | 10.8% |
| 桃園市八德區Bade District, Taoyuan City | 10.8% |
| 屏東縣三地門鄉Sandimen Township, Pingtung County | 10.7% |
| 屏東縣來義鄉Laiyi Township, Pingtung County | 10.7% |
| 台中市北屯區Beitun District, Taichung City | 10.7% |
| 新竹縣新豐鄉Xinfeng Township, Hsinchu County | 10.6% |
| 台東縣綠島鄉Ludao Township, Taitung County | 10.6% |
| 新北市樹林區Shulin District, New Taipei City | 10.6% |
| 桃園市楊梅區Yangmei District, Taoyuan City | 10.6% |
| 新北市五股區Wugu District, New Taipei City | 10.5% |
| 台中市沙鹿區Shalu District, Taichung City | 10.5% |
| 台中市龍井區Longjing District, Taichung City | 10.5% |
| 台中市太平區Taiping District, Taichung City | 10.5% |
| 桃園市桃園區Taoyuan District, Taoyuan City | 10.5% |
| 南投縣仁愛鄉Ren'ai Township, Nantou County | 10.4% |
| 新北市泰山區Taishan District, New Taipei City | 10.4% |
| 桃園市平鎮區Pingzhen District, Taoyuan City | 10.4% |
| 新北市新莊區Xinzhuang District, New Taipei City | 10.3% |
| 台南市安南區Annan District, Tainan City | 10.3% |
| 台中市潭子區Tanzi District, Taichung City | 10.2% |
| 連江縣南竿鄉Nangan Township, Lienchiang County | 10.1% |
| 新北市林口區Linkou District, New Taipei City | 10% |
| 台南市安平區Anping District, Tainan City | 10% |
| 新北市土城區Tucheng District, New Taipei City | 9.9% |
| 台南市永康區Yongkang District, Tainan City | 9.9% |
| 金門縣烏坵鄉Wuqiu Township, Kinmen County | 9.9% |
| 台中市西屯區Xitun District, Taichung City | 9.7% |
| 台中市大里區Dali District, Taichung City | 9.7% |
| 屏東縣泰武鄉Taiwu Township, Pingtung County | 9.6% |
| 新北市蘆洲區Luzhou District, New Taipei City | 9.4% |
| 花蓮縣卓溪鄉Zhuoxi Township, Hualien County | 9.2% |
| 宜蘭縣大同鄉Datong Township, Yilan County | 9.1% |
| 台東縣金峰鄉Jinfeng Township, Taitung County | 9.1% |
| 台中市大雅區Daya District, Taichung City | 9.1% |
| 台中市南屯區Nantun District, Taichung City | 8.9% |
| 桃園市蘆竹區Luzhu District, Taoyuan City | 8.9% |
| 宜蘭縣南澳鄉Nan'ao Township, Yilan County | 8.8% |
| 台東縣延平鄉Yanping Township, Taitung County | 8.5% |
| 花蓮縣萬榮鄉Wanrong Township, Hualien County | 8.4% |
| 高雄市茂林區Maolin District, Kaohsiung City | 8.3% |
| 新竹縣尖石鄉Jianshi Township, Hsinchu County | 8.2% |
| 花蓮縣秀林鄉Xiulin Township, Hualien County | 8.2% |
| 台東縣海端鄉Haiduan Township, Taitung County | 7.8% |
| 連江縣東引鄉Dongyin Township, Lienchiang County | 7.7% |
| 新竹縣竹北市Zhubei City, Hsinchu County | 7.6% |
| 高雄市桃源區Taoyuan District, Kaohsiung City | 7.4% |
| 台東縣蘭嶼鄉Lanyu Township, Taitung County | 7.3% |
| 高雄市那瑪夏區Namaxia District, Kaohsiung City | 7.1% |
來源：MOI 內政部戶政司 #77132 (village single-year age, 107/03)（2018 年）Source: MOI 內政部戶政司 #77132 (village single-year age, 107/03) (2018) ※ 4 個單元在地理檔中沒有對應圖形，僅列出來源代碼。 ※ 4 unit(s) have no matching shape in the geo file and are listed by source code only.
伊朗 (30)
伊朗 65 歲以上人口占比最高的一級行政區是 Gilan（8.9%），最低是 Sistan and Baluchestan（3.2%）；全國未加權平均 6%（Statistical Centre of Iran, 2016 census (via UN OCHA/HDX COD-PS mirror)，2016 年）。In 伊朗, the admin-1 unit with the highest share of population aged 65+ is Gilan at 8.9%, and the lowest is Sistan and Baluchestan at 3.2%; the unweighted national figure is 6% (Statistical Centre of Iran, 2016 census (via UN OCHA/HDX COD-PS mirror), 2016).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Gilan | 8.9% |
| Markazi | 7.6% |
| Mazandaran | 7.6% |
| Hamadan | 7.3% |
| East Azarbaijan | 7.2% |
完整列表Full list (30)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Gilan | 8.9% |
| Markazi | 7.6% |
| Mazandaran | 7.6% |
| Hamadan | 7.3% |
| East Azarbaijan | 7.2% |
| Esfahan | 7.1% |
| South Khorasan | 6.9% |
| Semnan | 6.7% |
| Zanjan | 6.7% |
| Alborz | 6.6% |
| Kermanshah | 6.5% |
| Ardebil | 6.4% |
| Fars | 6.1% |
| Kordestan | 6.1% |
| Qazvin | 6% |
| Lorestan | 5.9% |
| Yazd | 5.9% |
| Chahar Mahall and Bakhtiari | 5.8% |
| Ilam | 5.6% |
| Razavi Khorasan | 5.6% |
| West Azarbaijan | 5.6% |
| North Khorasan | 5.5% |
| Kerman | 5.1% |
| Golestan | 5% |
| Qom | 4.9% |
| Kohgiluyeh and Buyer Ahmad | 4.6% |
| Khuzestan | 4.4% |
| Bushehr | 4.2% |
| Hormozgan | 3.9% |
| Sistan and Baluchestan | 3.2% |
來源：Statistical Centre of Iran, 2016 census (via UN OCHA/HDX COD-PS mirror)（2016 年）Source: Statistical Centre of Iran, 2016 census (via UN OCHA/HDX COD-PS mirror) (2016)
印尼 (33)
印尼 65 歲以上人口占比最高的一級行政區是 Yogyakarta（9.5%），最低是 Papua（1.2%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 印尼, the admin-1 unit with the highest share of population aged 65+ is Yogyakarta at 9.5%, and the lowest is Papua at 1.2% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Yogyakarta | 9.5% |
| Jawa Tengah | 8.5% |
| Jawa Timur | 8.1% |
| Bali | 7.6% |
| Sumatera Barat | 6.5% |
完整列表Full list (33)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Yogyakarta | 9.5% |
| Jawa Tengah | 8.5% |
| Jawa Timur | 8.1% |
| Bali | 7.6% |
| Sumatera Barat | 6.5% |
| Sulawesi Utara | 6.4% |
| Sulawesi Selatan | 6.3% |
| Nusa Tenggara Timur | 5.8% |
| Lampung | 5.6% |
| Nusa Tenggara Barat | 5.3% |
| Jawa Barat | 4.9% |
| Maluku | 4.7% |
| Sulawesi Barat | 4.7% |
| Sumatera Selatan | 4.7% |
| Bengkulu | 4.7% |
| Sumatera Utara | 4.5% |
| Aceh | 4.5% |
| Sulawesi Tenggara | 4.4% |
| Jambi | 4.3% |
| Bangka-Belitung | 4.3% |
| Kalimantan Barat | 4.2% |
| Sulawesi Tengah | 4.2% |
| Gorontalo | 4.2% |
| Kalimantan Selatan | 4.2% |
| Jakarta Raya | 3.6% |
| Banten | 3.5% |
| Kalimantan Tengah | 3.5% |
| Maluku Utara | 3.4% |
| Riau | 3.2% |
| Kalimantan Timur | 2.8% |
| Kepulauan Riau | 2.4% |
| Papua Barat | 2% |
| Papua | 1.2% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
印度 (36)
印度 65 歲以上人口占比最高的一級行政區是 Kerala（8.3%），最低是 Dadra and Nagar Haveli and Daman and Diu（2.6%）；全國未加權平均 5.1%（Census of India 2011, table C-14 (five-year age groups by state)，2011 年）。In 印度, the admin-1 unit with the highest share of population aged 65+ is Kerala at 8.3%, and the lowest is Dadra and Nagar Haveli and Daman and Diu at 2.6%; the unweighted national figure is 5.1% (Census of India 2011, table C-14 (five-year age groups by state), 2011).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Kerala | 8.3% |
| Goa | 7% |
| Himachal Pradesh | 6.9% |
| Punjab | 6.7% |
| Maharashtra | 6.6% |
完整列表Full list (36)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Kerala | 8.3% |
| Goa | 7% |
| Himachal Pradesh | 6.9% |
| Punjab | 6.7% |
| Maharashtra | 6.6% |
| Tamil Nadu | 6.6% |
| Karnataka | 6.1% |
| Puducherry | 6.1% |
| Odisha | 6% |
| Andhra Pradesh | 6% |
| Telangana | 6% |
| Uttarakhand | 5.7% |
| West Bengal | 5.5% |
| Haryana | 5.3% |
| Tripura | 5.2% |
| Madhya Pradesh | 5.1% |
| Gujarat | 5.1% |
| Lakshadweep | 5% |
| Rajasthan | 4.9% |
| Uttar Pradesh | 4.9% |
| Chhattisgarh | 4.9% |
| Jammu and Kashmir | 4.8% |
| Ladakh | 4.8% |
| Bihar | 4.5% |
| Sikkim | 4.5% |
| Manipur | 4.5% |
| Assam | 4.2% |
| Jharkhand | 4.2% |
| Delhi | 4% |
| Mizoram | 4% |
| Andaman and Nicobar | 4% |
| Chandigarh | 3.9% |
| Nagaland | 3.3% |
| Meghalaya | 3% |
| Arunachal Pradesh | 2.8% |
| Dadra and Nagar Haveli and Daman and Diu | 2.6% |
來源：Census of India 2011, table C-14 (five-year age groups by state)（2011 年）Source: Census of India 2011, table C-14 (five-year age groups by state) (2011)
西班牙 (50)
西班牙 65 歲以上人口占比最高的一級行政區是 Orense（31.9%），最低是 Melilla（11.7%）；全國未加權平均 21.7%（Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3，2023 年）。In 西班牙, the admin-1 unit with the highest share of population aged 65+ is Orense at 31.9%, and the lowest is Melilla at 11.7%; the unweighted national figure is 21.7% (Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3, 2023).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Orense | 31.9% |
| Zamora | 31.9% |
| Lugo | 30% |
| León | 28.5% |
| Asturias | 27.6% |
完整列表Full list (50)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Orense | 31.9% |
| Zamora | 31.9% |
| Lugo | 30% |
| León | 28.5% |
| Asturias | 27.6% |
| Salamanca | 27.5% |
| Palencia | 27.2% |
| Ávila | 26.5% |
| La Coruña | 25.7% |
| Soria | 25.4% |
| Burgos | 25% |
| Valladolid | 24.4% |
| Teruel | 24.2% |
| Cáceres | 24.2% |
| Pontevedra | 23.9% |
| Bizkaia | 23.9% |
| Cantabria | 23.5% |
| Gipuzkoa | 23.3% |
| Segovia | 23.1% |
| Cuenca | 23% |
| Huesca | 22.7% |
| Álava | 22.2% |
| La Rioja | 21.8% |
| Zaragoza | 21.7% |
| Ciudad Real | 20.9% |
| Alicante | 20.7% |
| Badajoz | 20.5% |
| Córdoba | 20.5% |
| Navarra | 20.4% |
| Jaén | 20.4% |
| Albacete | 19.9% |
| Castellón | 19.9% |
| Lérida | 19.7% |
| Valencia | 19.7% |
| Tarragona | 19.6% |
| Barcelona | 19.4% |
| Granada | 19% |
| Gerona | 18.6% |
| Madrid | 18.4% |
| Málaga | 18.3% |
| Toledo | 18.2% |
| Cádiz | 18.1% |
| Huelva | 17.6% |
| Sevilla | 17.6% |
| Guadalajara | 16.5% |
| Murcia | 16.3% |
| Baleares | 16.1% |
| Almería | 15.6% |
| Ceuta | 12.8% |
| Melilla | 11.7% |
來源：Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3（2023 年）Source: Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3 (2023)
孟加拉 (7)
孟加拉 65 歲以上人口占比最高的一級行政區是 Barisal（6.3%），最低是 Dhaka（4.7%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 孟加拉, the admin-1 unit with the highest share of population aged 65+ is Barisal at 6.3%, and the lowest is Dhaka at 4.7% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Barisal | 6.3% |
| Khulna | 5.9% |
| Rajshahi | 5.2% |
| Chittagong | 5.1% |
| Rangpur | 5.1% |
完整列表Full list (7)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Barisal | 6.3% |
| Khulna | 5.9% |
| Rajshahi | 5.2% |
| Chittagong | 5.1% |
| Rangpur | 5.1% |
| Sylhet | 5% |
| Dhaka | 4.7% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
法國 (94)
法國 65 歲以上人口占比最高的一級行政區是 Lot（31.8%），最低是 Seine-Saint-Denis（13.1%）；全國未加權平均 23.7%（Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3，2023 年）。In 法國, the admin-1 unit with the highest share of population aged 65+ is Lot at 31.8%, and the lowest is Seine-Saint-Denis at 13.1%; the unweighted national figure is 23.7% (Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3, 2023).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Lot | 31.8% |
| Creuse | 31.7% |
| Nièvre | 30.8% |
| Dordogne | 30.4% |
| Cantal | 29.6% |
完整列表Full list (94)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Lot | 31.8% |
| Creuse | 31.7% |
| Nièvre | 30.8% |
| Dordogne | 30.4% |
| Cantal | 29.6% |
| Charente-Maritime | 29.4% |
| Indre | 29.3% |
| Corrèze | 28.8% |
| Gers | 28.8% |
| Allier | 28.8% |
| Aveyron | 28.2% |
| Hautes-Pyrénées | 27.8% |
| Orne | 27.6% |
| Aude | 27.6% |
| Lot-et-Garonne | 27.5% |
| Alpes-de-Haute-Provence | 27.5% |
| Var | 27.4% |
| Côtes-d'Armor | 27.3% |
| Ariège | 27.3% |
| Saône-et-Loire | 27.2% |
| Hautes-Alpes | 27.1% |
| Lozère | 27% |
| Pyrénées-Orientales | 27% |
| Cher | 26.8% |
| Haute-Marne | 26.7% |
| Landes | 26.7% |
| Charente | 26.7% |
| Tarn | 26.6% |
| Manche | 26.4% |
| Vendée | 26.4% |
| Morbihan | 26.4% |
| Loir-et-Cher | 26.2% |
| Ardèche | 26.2% |
| Haute-Vienne | 26.1% |
| Vosges | 25.8% |
| Haute-Loire | 25.8% |
| Yonne | 25.6% |
| Pyrénées-Atlantiques | 25.4% |
| Alpes-Maritimes | 25.1% |
| Meuse | 25% |
| Haute-Corse | 24.9% |
| Jura | 24.8% |
| Haute-Saône | 24.8% |
| Finistère | 24.8% |
| Deux-Sèvres | 24.6% |
| Corse-du-Sud | 24.6% |
| Gard | 24.5% |
| Vaucluse | 23.8% |
| Mayenne | 23.4% |
| Calvados | 23.3% |
| Sarthe | 23.2% |
| Tarn-et-Garonne | 23.2% |
| Loire | 23.2% |
| Ardennes | 23.1% |
| Vienne | 23.1% |
| Drôme | 23.1% |
| Indre-et-Loire | 22.9% |
| Puy-de-Dôme | 22.9% |
| Aube | 22.7% |
| Hérault | 22.7% |
| Côte-d'Or | 22.2% |
| Aisne | 21.9% |
| Savoie | 21.9% |
| Eure-et-Loir | 21.7% |
| Bouches-du-Rhône | 21.5% |
| Seine-Maritime | 21.4% |
| Somme | 21.4% |
| Loiret | 21.2% |
| Marne | 21.2% |
| Moselle | 21.2% |
| Maine-et-Loire | 21.1% |
| Territoire de Belfort | 20.9% |
| Eure | 20.8% |
| Doubs | 20.6% |
| Meurthe-et-Moselle | 20.5% |
| Pas-de-Calais | 20.4% |
| Gironde | 20.1% |
| Bas-Rhin | 19.8% |
| Isère | 19.5% |
| Loire-Atlantique | 19.3% |
| Ille-et-Vilaine | 18.8% |
| Ain | 18.8% |
| Nord | 18.4% |
| Oise | 18.3% |
| Paris | 18.1% |
| Haute-Savoie | 17.7% |
| Rhône | 17.6% |
| Haute-Garonne | 17.3% |
| Yvelines | 17.1% |
| Essonne | 15.9% |
| Hauts-de-Seine | 15.9% |
| Val-de-Marne | 15.8% |
| Val-d'Oise | 14.7% |
| Seine-Saint-Denis | 13.1% |
來源：Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3（2023 年）Source: Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3 (2023)
波蘭 (16)
波蘭 65 歲以上人口占比最高的一級行政區是 Świętokrzyskie（22.5%），最低是 Lesser Poland（18.3%）；全國未加權平均 20.2%（Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-2，2023 年）。In 波蘭, the admin-1 unit with the highest share of population aged 65+ is Świętokrzyskie at 22.5%, and the lowest is Lesser Poland at 18.3%; the unweighted national figure is 20.2% (Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-2, 2023).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Świętokrzyskie | 22.5% |
| Łódź | 22% |
| West Pomeranian | 21.2% |
| Lublin | 21.1% |
| Silesian | 21% |
完整列表Full list (16)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Świętokrzyskie | 22.5% |
| Łódź | 22% |
| West Pomeranian | 21.2% |
| Lublin | 21.1% |
| Silesian | 21% |
| Opole | 21% |
| Lower Silesian | 20.8% |
| Lubusz | 20.1% |
| Kuyavian-Pomeranian | 20.1% |
| Podlachian | 20.1% |
| Warmian-Masurian | 19.6% |
| Subcarpathian | 19.3% |
| Masovian | 18.9% |
| Greater Poland | 18.4% |
| Pomeranian | 18.4% |
| Lesser Poland | 18.3% |
來源：Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-2（2023 年）Source: Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-2 (2023)
南韓 (15)
南韓 65 歲以上人口占比最高的一級行政區是 경상북도（28.5%），最低是 세종특별자치시（12.8%）；全國未加權平均 22.5%（KOSIS 고령인구비율 (DT_1YL20631), 2026-07，2026 年）。In 南韓, the admin-1 unit with the highest share of population aged 65+ is North Gyeongsang at 28.5%, and the lowest is Sejong at 12.8%; the unweighted national figure is 22.5% (KOSIS 고령인구비율 (DT_1YL20631), 2026-07, 2026).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 경상북도North Gyeongsang | 28.5% |
| 강원도Gangwon | 27.8% |
| 전라북도North Jeolla | 27.5% |
| 부산광역시Busan | 26.1% |
| 충청남도South Chungcheong | 24.3% |
完整列表Full list (15)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| 경상북도North Gyeongsang | 28.5% |
| 강원도Gangwon | 27.8% |
| 전라북도North Jeolla | 27.5% |
| 부산광역시Busan | 26.1% |
| 충청남도South Chungcheong | 24.3% |
| 경상남도South Gyeongsang | 24.2% |
| 충청북도North Chungcheong | 24% |
| 대구광역시Daegu | 22.9% |
| 서울특별시Seoul | 21.1% |
| 제주특별자치도Jeju | 20.7% |
| 대전광역시Daejeon | 19.9% |
| 인천광역시Incheon | 19.7% |
| 울산광역시Ulsan | 19.6% |
| 경기도Gyeonggi | 18.5% |
| 세종특별자치시Sejong | 12.8% |
來源：KOSIS 고령인구비율 (DT_1YL20631), 2026-07（2026 年）Source: KOSIS 고령인구비율 (DT_1YL20631), 2026-07 (2026)
美國 (51)
美國 65 歲以上人口占比最高的一級行政區是 Maine（22.4%），最低是 Utah（11.9%）；全國未加權平均 17.7%（US Census ACS 5-year 2024 (S0101_C02_030E)，2024 年）。In 美國, the admin-1 unit with the highest share of population aged 65+ is Maine at 22.4%, and the lowest is Utah at 11.9%; the unweighted national figure is 17.7% (US Census ACS 5-year 2024 (S0101_C02_030E), 2024).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Maine | 22.4% |
| Vermont | 21.4% |
| Florida | 21.3% |
| West Virginia | 21% |
| Delaware | 20.6% |
完整列表Full list (51)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Maine | 22.4% |
| Vermont | 21.4% |
| Florida | 21.3% |
| West Virginia | 21% |
| Delaware | 20.6% |
| Hawaii | 20.5% |
| Montana | 20.1% |
| New Hampshire | 20.1% |
| Pennsylvania | 19.5% |
| New Mexico | 19.3% |
| Oregon | 19.1% |
| Arizona | 18.9% |
| South Carolina | 18.9% |
| Rhode Island | 18.7% |
| Michigan | 18.6% |
| Connecticut | 18.5% |
| Wisconsin | 18.5% |
| Wyoming | 18.5% |
| Ohio | 18.3% |
| Iowa | 18.1% |
| South Dakota | 18% |
| Massachusetts | 17.9% |
| Missouri | 17.9% |
| New York | 17.9% |
| Alabama | 17.8% |
| Arkansas | 17.6% |
| Kentucky | 17.3% |
| Minnesota | 17.3% |
| Mississippi | 17.2% |
| New Jersey | 17.2% |
| North Carolina | 17.2% |
| Tennessee | 17.1% |
| Idaho | 17% |
| Illinois | 17% |
| Kansas | 17% |
| Nevada | 17% |
| Indiana | 16.8% |
| Louisiana | 16.7% |
| Maryland | 16.7% |
| Nebraska | 16.7% |
| Virginia | 16.7% |
| Washington | 16.6% |
| North Dakota | 16.5% |
| Oklahoma | 16.3% |
| California | 15.7% |
| Colorado | 15.6% |
| Georgia | 15% |
| Alaska | 13.8% |
| Texas | 13.4% |
| District of Columbia | 12.8% |
| Utah | 11.9% |
來源：US Census ACS 5-year 2024 (S0101_C02_030E)（2024 年）Source: US Census ACS 5-year 2024 (S0101_C02_030E) (2024)
英國 (170)
英國 65 歲以上人口占比最高的一級行政區是 Dorset（30.5%），最低是 Tower Hamlets（5.9%）；全國未加權平均 18.5%（ONS mid-year population estimates via Nomis (NM_2002_1)，2024 年）。In 英國, the admin-1 unit with the highest share of population aged 65+ is Dorset at 30.5%, and the lowest is Tower Hamlets at 5.9%; the unweighted national figure is 18.5% (ONS mid-year population estimates via Nomis (NM_2002_1), 2024).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Dorset | 30.5% |
| Isle of Wight | 30.2% |
| Powys | 28.9% |
| Conwy | 28.3% |
| Dumfries and Galloway | 28% |
完整列表Full list (170)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Dorset | 30.5% |
| Isle of Wight | 30.2% |
| Powys | 28.9% |
| Conwy | 28.3% |
| Dumfries and Galloway | 28% |
| Argyll and Bute | 27.7% |
| Scottish Borders | 27.4% |
| Torbay | 27.3% |
| South Ayrshire | 27.3% |
| East Riding of Yorkshire | 27.1% |
| Herefordshire | 27% |
| Pembrokeshire | 27% |
| Northumberland | 26.6% |
| Monmouthshire | 26.6% |
| Rutland | 26.4% |
| Shropshire | 26.4% |
| Ceredigion | 26.4% |
| Cornwall | 26% |
| Angus | 25.9% |
| Isles of Scilly | 25.2% |
| Denbighshire | 25.1% |
| Carmarthenshire | 25.1% |
| East Dunbartonshire | 24.9% |
| Highland | 24.6% |
| Redcar and Cleveland | 24% |
| North Somerset | 24% |
| Sefton | 23.7% |
| Moray | 23.6% |
| Gwynedd | 23.4% |
| Inverclyde | 23% |
| North Lincolnshire | 22.9% |
| Wiltshire | 22.9% |
| Vale of Glamorgan | 22.7% |
| Cheshire East | 22.5% |
| Shetland Islands | 22.4% |
| Fife | 22.3% |
| Flintshire | 22.1% |
| Aberdeenshire | 22.1% |
| East Ayrshire | 22.1% |
| East Renfrewshire | 22% |
| Neath Port Talbot | 21.8% |
| East Lothian | 21.8% |
| Cheshire West and Chester | 21.6% |
| North East Lincolnshire | 21.6% |
| South Tyneside | 21.5% |
| Bridgend | 21.5% |
| Clackmannanshire | 21.4% |
| Solihull | 21.3% |
| Darlington | 21.2% |
| North Tyneside | 21.2% |
| Torfaen | 21.2% |
| Stirling | 21.1% |
| Blackpool | 20.8% |
| Wrexham | 20.8% |
| South Lanarkshire | 20.8% |
| West Dunbartonshire | 20.8% |
| Sunderland | 20.7% |
| Caerphilly | 20.7% |
| Blaenau Gwent | 20.7% |
| Gateshead | 20.4% |
| West Berkshire | 20.3% |
| Swansea | 20.3% |
| Dudley | 20.2% |
| Stockport | 20.1% |
| Barnsley | 20.1% |
| Hartlepool | 20% |
| Rhondda, Cynon, Taff | 20% |
| Falkirk | 20% |
| Renfrewshire | 20% |
| Warrington | 19.8% |
| Rotherham | 19.7% |
| Doncaster | 19.6% |
| Calderdale | 19.6% |
| Merthyr Tydfil | 19.6% |
| Stockton-on-Tees | 19.5% |
| Bath and North East Somerset | 19.5% |
| Midlothian | 19.4% |
| Halton | 19.3% |
| Wigan | 19.3% |
| Southend-on-Sea | 19.3% |
| York | 19.2% |
| Wakefield | 19.1% |
| Buckinghamshire | 19.1% |
| Plymouth | 18.9% |
| South Gloucestershire | 18.6% |
| North Lanarkshire | 18.5% |
| Bury | 18.3% |
| Central Bedfordshire | 18.2% |
| Kirklees | 18.1% |
| Telford and Wrekin | 17.9% |
| Bromley | 17.9% |
| West Lothian | 17.9% |
| Tameside | 17.6% |
| Trafford | 17.6% |
| St Albans | 17.6% |
| Northamptonshire | 17.5% |
| Wokingham | 17.4% |
| Knowsley | 17.3% |
| Havering | 17.3% |
| Walsall | 17.1% |
| Bedford | 17.1% |
| Stoke-on-Trent | 17% |
| Richmond upon Thames | 17% |
| Bolton | 16.9% |
| Sheffield | 16.8% |
| Newport | 16.8% |
| Middlesbrough | 16.6% |
| Bexley | 16.6% |
| Rochdale | 16.4% |
| Medway | 16.4% |
| Swindon | 16.3% |
| Derby | 16.2% |
| Edinburgh | 16.1% |
| Wolverhampton | 16% |
| Bracknell Forest | 16% |
| Mid Ulster | 15.9% |
| Oldham | 15.7% |
| Harrow | 15.7% |
| Leeds | 15.6% |
| Kingston upon Hull | 15.5% |
| Bradford | 15.5% |
| Kensington and Chelsea | 15.4% |
| Liverpool | 15.3% |
| Sutton | 15.3% |
| Belfast | 15.2% |
| Barnet | 15% |
| Kingston upon Thames | 15% |
| Portsmouth | 14.9% |
| Newcastle upon Tyne | 14.8% |
| Enfield | 14.7% |
| Cardiff | 14.6% |
| Sandwell | 14.5% |
| Peterborough | 14.4% |
| Blackburn with Darwen | 14.3% |
| Brighton and Hove | 14.3% |
| Milton Keynes | 14.2% |
| Coventry | 13.9% |
| Croydon | 13.9% |
| Southampton | 13.7% |
| Thurrock | 13.5% |
| Merton | 13.2% |
| Hillingdon | 13.1% |
| Birmingham | 13% |
| Salford | 12.6% |
| Westminster | 12.6% |
| Ealing | 12.6% |
| Redbridge | 12.6% |
| Bristol | 12.6% |
| Brent | 12.2% |
| Hounslow | 12.2% |
| Reading | 12.2% |
| Camden | 12.1% |
| Leicester | 12% |
| Nottingham | 11.8% |
| Luton | 11.4% |
| Haringey | 11.3% |
| Hammersmith and Fulham | 10.9% |
| Greenwich | 10.8% |
| Waltham Forest | 10.7% |
| Lewisham | 10.3% |
| Wandsworth | 9.9% |
| Slough | 9.8% |
| Islington | 9.7% |
| Lambeth | 9.5% |
| Manchester | 9.3% |
| Southwark | 9.1% |
| Barking and Dagenham | 8.6% |
| Hackney | 8.5% |
| Newham | 7.5% |
| Tower Hamlets | 5.9% |
來源：ONS mid-year population estimates via Nomis (NM_2002_1)（2024 年）Source: ONS mid-year population estimates via Nomis (NM_2002_1) (2024)
泰國 (77)
泰國 65 歲以上人口占比最高的一級行政區是 จังหวัดอ่างทอง（19.6%），最低是 จังหวัดสมุทรปราการ（8.5%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 泰國, the admin-1 unit with the highest share of population aged 65+ is Ang Thong at 19.6%, and the lowest is Samut Prakan at 8.5% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| จังหวัดอ่างทองAng Thong | 19.6% |
| จังหวัดสิงห์บุรีSing Buri | 19.5% |
| จังหวัดสมุทรสงครามSamut Songkhram | 18.8% |
| จังหวัดชัยนาทChai Nat | 18.3% |
| จังหวัดลำพูนLamphun | 17.4% |
完整列表Full list (77)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| จังหวัดอ่างทองAng Thong | 19.6% |
| จังหวัดสิงห์บุรีSing Buri | 19.5% |
| จังหวัดสมุทรสงครามSamut Songkhram | 18.8% |
| จังหวัดชัยนาทChai Nat | 18.3% |
| จังหวัดลำพูนLamphun | 17.4% |
| จังหวัดนครนายกNakhon Nayok | 16.6% |
| จังหวัดลำปางLampang | 16.6% |
| จังหวัดพิจิตรPhichit | 16.6% |
| จังหวัดสุพรรณบุรีSuphan Buri | 16.5% |
| จังหวัดเพชรบุรีPhetchaburi | 16.4% |
| จังหวัดพระนครศรีอยุธยาPhra Nakhon Si Ayutthaya | 16.3% |
| จังหวัดอุตรดิตถ์Uttaradit | 16.2% |
| จังหวัดอุทัยธานีUthai Thani | 15.9% |
| จังหวัดเชียงใหม่Chiang Mai | 15.8% |
| จังหวัดราชบุรีRatchaburi | 15.7% |
| จังหวัดพัทลุงPhatthalung | 15.6% |
| จังหวัดนครศรีธรรมราชNakhon Si Thammarat | 15.5% |
| จังหวัดนครสวรรค์Nakhon Sawan | 15.5% |
| จังหวัดปราจีนบุรีPrachin Buri | 15.1% |
| ลพบุรีLop Buri | 15% |
| จังหวัดสุโขทัยSukhothai | 15% |
| จังหวัดแพร่Phrae | 15% |
| จังหวัดชุมพรChumphon | 14.9% |
| จังหวัดพะเยาPhayao | 14.4% |
| จังหวัดฉะเชิงเทราChachoengsao | 14.4% |
| จังหวัดสระบุรีSaraburi | 13.9% |
| จังหวัดพิษณุโลกPhitsanulok | 13.8% |
| จังหวัดตรังTrang | 13.8% |
| อำเภอเมืองเพชรบูรณ์Phetchabun | 13.7% |
| จังหวัดสงขลาSongkhla | 13.6% |
| จังหวัดเชียงรายChiang Rai | 13.6% |
| จังหวัดน่านNan | 13.6% |
| จังหวัดพังงาPhangnga | 13.6% |
| จังหวัดสุราษฎร์ธานีSurat Thani | 13.6% |
| จันทบุรีChanthaburi | 13.5% |
| จังหวัดนครราชสีมาNakhon Ratchasima | 13.4% |
| จังหวัดสุรินทร์Surin | 13.2% |
| จังหวัดปัตตานีPattani | 13.2% |
| จังหวัดกำแพงเพชรKamphaeng Phet | 13.2% |
| จังหวัดชัยนาทChaiyaphum | 13.1% |
| จังหวัดตราดTrat | 12.9% |
| จังหวัดประจวบคีรีขันธ์Prachuap Khiri Khan | 12.8% |
| จังหวัดยโสธรYasothon | 12.8% |
| จังหวัดเลยLoei | 12.7% |
| อำเภอเมืองนครปฐมNakhon Pathom | 12.7% |
| จังหวัดอุบลราชธานีUbon Ratchathani | 12.3% |
| จังหวัดอำนาจเจริญAmnat Charoen | 12.3% |
| จังหวัดศรีสะเกษSi Sa Ket | 12.1% |
| จังหวัดบุรีรัมย์Buri Ram | 12% |
| อำเภอเมืองกาญจนบุรีKanchanaburi | 11.9% |
| ร้อยเอ็ดRoi Et | 11.6% |
| จังหวัดมุกดาหารMukdahan | 11.5% |
| จังหวัดนนทบุรีNonthaburi | 11.4% |
| จังหวัดสตูลSatun | 11.3% |
| จังหวัดตากTak | 11.3% |
| จังหวัดขอนแก่นKhon Kaen | 11.3% |
| จังหวัดนครพนมNakhon Phanom | 11.2% |
| จังหวัดแม่ฮ่องสอนMae Hong Son | 11.1% |
| จังหวัดสระแก้วSa Kaeo | 11% |
| จังหวัดนราธิวาสNarathiwat | 11% |
| จังหวัดชลบุรีChon Buri | 11% |
| จังหวัดระนองRanong | 10.9% |
| จังหวัดหนองคายNong Khai | 10.8% |
| จังหวัดกระบี่Krabi | 10.8% |
| จังหวัดมหาสารคามMaha Sarakham | 10.7% |
| จังหวัดระยองRayong | 10.6% |
| จังหวัดหนองคายBueng Kan | 10.5% |
| จังหวัดกาฬสินธุ์Kalasin | 10.5% |
| จังหวัดยะลาYala | 10.4% |
| จังหวัดเชียงใหม่Bangkok Metropolis | 10.1% |
| จังหวัดหนองบัวลำภูNong Bua Lam Phu | 10% |
| จังหวัดสมุทรสาครSamut Sakhon | 9.8% |
| จังหวัดปทุมธานีPathum Thani | 9.6% |
| จังหวัดสกลนครSakon Nakhon | 9.5% |
| จังหวัดอุดรธานีUdon Thani | 9.5% |
| จังหวัดภูเก็ตPhuket | 9.2% |
| จังหวัดสมุทรปราการSamut Prakan | 8.5% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
紐西蘭 (16)
紐西蘭 65 歲以上人口占比最高的一級行政區是 Tasman District（24.5%），最低是 Auckland（13.4%）；全國未加權平均 19.8%（Stats NZ subnational population estimates, 30 June 2025 (Table 3)，2025 年）。In 紐西蘭, the admin-1 unit with the highest share of population aged 65+ is Tasman District at 24.5%, and the lowest is Auckland at 13.4%; the unweighted national figure is 19.8% (Stats NZ subnational population estimates, 30 June 2025 (Table 3), 2025).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Tasman District | 24.5% |
| Marlborough District | 24.4% |
| West Coast | 23.9% |
| Northland | 22.6% |
| Nelson City | 22.5% |
完整列表Full list (16)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Tasman District | 24.5% |
| Marlborough District | 24.4% |
| West Coast | 23.9% |
| Northland | 22.6% |
| Nelson City | 22.5% |
| Manawatu-Wanganui | 20.1% |
| Hawke's Bay | 19.8% |
| Taranaki | 19.8% |
| Bay of Plenty | 19.6% |
| Southland | 18.8% |
| Otago | 18.2% |
| Canterbury | 17.7% |
| Waikato | 17.6% |
| Gisborne District | 17.1% |
| Wellington | 16.2% |
| Auckland | 13.4% |
來源：Stats NZ subnational population estimates, 30 June 2025 (Table 3)（2025 年）Source: Stats NZ subnational population estimates, 30 June 2025 (Table 3) (2025)
馬來西亞 (16)
馬來西亞 65 歲以上人口占比最高的一級行政區是 Perlis（11.6%），最低是 Labuan（4.1%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 馬來西亞, the admin-1 unit with the highest share of population aged 65+ is Perlis at 11.6%, and the lowest is Labuan at 4.1% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Perlis | 11.6% |
| Perak | 10.2% |
| Kedah | 8.9% |
| Kelantan | 8.8% |
| Melaka | 8.7% |
完整列表Full list (16)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Perlis | 11.6% |
| Perak | 10.2% |
| Kedah | 8.9% |
| Kelantan | 8.8% |
| Melaka | 8.7% |
| Pulau Pinang | 8.5% |
| Negeri Sembilan | 8.3% |
| Sarawak | 8% |
| Johor | 7% |
| Terengganu | 6.8% |
| Pahang | 6% |
| Selangor | 5.1% |
| Kuala Lumpur | 5% |
| Putrajaya | 5% |
| Sabah | 4.2% |
| Labuan | 4.1% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
菲律賓 (82)
菲律賓 65 歲以上人口占比最高的一級行政區是 Siquijor（10.9%），最低是 Tawi-Tawi（1.9%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 菲律賓, the admin-1 unit with the highest share of population aged 65+ is Siquijor at 10.9%, and the lowest is Tawi-Tawi at 1.9% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Siquijor | 10.9% |
| Ilocos Sur | 8.7% |
| Ilocos Norte | 8.7% |
| Southern Leyte | 8.4% |
| Abra | 8.4% |
完整列表Full list (82)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Siquijor | 10.9% |
| Ilocos Sur | 8.7% |
| Ilocos Norte | 8.7% |
| Southern Leyte | 8.4% |
| Abra | 8.4% |
| Bohol | 8.3% |
| Antique | 8.1% |
| Catanduanes | 8.1% |
| Camiguin | 8% |
| Eastern Samar | 7.8% |
| Aklan | 7.7% |
| Iloilo | 7.6% |
| La Union | 7.3% |
| Mountain Province | 7.1% |
| Biliran | 7% |
| Guimaras | 7% |
| Marinduque | 7% |
| Romblon | 6.9% |
| Misamis Occidental | 6.7% |
| Dagupan | 6.5% |
| Cagayan | 6.5% |
| Capiz | 6.5% |
| Ormoc | 6.3% |
| Surigao del Norte | 6.2% |
| Albay | 6.2% |
| Sorsogon | 6.2% |
| Negros Oriental | 6.2% |
| Samar | 6% |
| Batangas | 5.9% |
| Ifugao | 5.8% |
| Tarlac | 5.8% |
| Naga | 5.7% |
| Cebu | 5.7% |
| Nueva Ecija | 5.7% |
| Negros Occidental | 5.6% |
| Northern Samar | 5.5% |
| Bacolod | 5.4% |
| Masbate | 5.4% |
| Nueva Vizcaya | 5.4% |
| Surigao del Sur | 5.3% |
| Zambales | 5.3% |
| Apayao | 5.3% |
| Lucena | 5.2% |
| Camarines Norte | 5.2% |
| Butuan | 5% |
| Angeles | 5% |
| Santiago | 4.9% |
| Kalinga | 4.8% |
| Cagayan de Oro | 4.7% |
| Davao Oriental | 4.7% |
| Aurora | 4.7% |
| Bataan | 4.7% |
| Mindoro Oriental | 4.7% |
| Quirino | 4.7% |
| Davao del Sur | 4.6% |
| Zamboanga del Sur | 4.5% |
| Zamboanga | 4.4% |
| Bulacan | 4.4% |
| Laguna | 4.3% |
| Davao | 4.2% |
| Compostela Valley | 4.2% |
| Baguio | 4.2% |
| Zamboanga Sibugay | 4.1% |
| Cotabato | 4.1% |
| Cavite | 4.1% |
| Mindoro Occidental | 4.1% |
| Puerto Princesa | 3.8% |
| Sultan Kudarat | 3.8% |
| San Juan | 3.8% |
| Lapu-Lapu | 3.8% |
| South Cotabato | 3.7% |
| Basilan | 3.7% |
| Mandaue | 3.7% |
| Agusan del Sur | 3.7% |
| Bukidnon | 3.7% |
| Lanao del Norte | 3.5% |
| Rizal | 3.5% |
| Sarangani | 3.4% |
| Maguindanao | 2.8% |
| Sulu | 2.6% |
| Lanao del Sur | 2.5% |
| Tawi-Tawi | 1.9% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
越南 (63)
越南 65 歲以上人口占比最高的一級行政區是 Thái Bình（11.9%），最低是 Đắk Nông（3.8%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 越南, the admin-1 unit with the highest share of population aged 65+ is Thái Bình at 11.9%, and the lowest is Đắk Nông at 3.8% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Thái Bình | 11.9% |
| Ha Tinh | 11.5% |
| Hà Nam | 11.3% |
| Quảng Ngãi | 11.1% |
| Đồng Bằng Sông Hồng | 11% |
完整列表Full list (63)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Thái Bình | 11.9% |
| Ha Tinh | 11.5% |
| Hà Nam | 11.3% |
| Quảng Ngãi | 11.1% |
| Đồng Bằng Sông Hồng | 11% |
| Quàng Nam | 10.8% |
| Hải Dương | 10.7% |
| Quảng Trị | 10.6% |
| Nam Định | 10.5% |
| Bình Định | 10.3% |
| Ninh Bình | 10.1% |
| Thừa Thiên - Huế | 10% |
| Thanh Hóa | 9.8% |
| Bến Tre | 9.7% |
| Quảng Bình | 9.6% |
| Phú Thọ | 9.6% |
| Hải Phòng | 9.5% |
| Bắc Ninh | 9.3% |
| Nghệ An | 9.2% |
| Vĩnh Phúc | 9.1% |
| Ha Noi | 9% |
| Cao Bằng | 8.8% |
| Tiền Giang | 8.7% |
| Phú Yên | 8.4% |
| Bắc Giang | 8.4% |
| Vĩnh Long | 8.3% |
| Long An | 8.1% |
| Quảng Ninh | 8.1% |
| Thái Nguyên | 7.9% |
| Đà Nẵng | 7.8% |
| Lạng Sơn | 7.7% |
| Khánh Hòa | 7.7% |
| Đông Bắc | 7.7% |
| Ðong Tháp | 7.6% |
| Trà Vinh | 7.6% |
| An Giang | 7.4% |
| Yên Bái | 7.4% |
| Can Tho | 7.4% |
| Hòa Bình | 7.3% |
| Tây Ninh | 7.2% |
| Hau Giang | 7.2% |
| Tuyên Quang | 7.2% |
| Sóc Trăng | 7% |
| Bình Thuận | 6.9% |
| Ninh Thuận | 6.6% |
| Bạc Liêu | 6.5% |
| Bà Rịa - Vũng Tàu | 6.3% |
| Kiên Giang | 6.2% |
| Hồ Chí Minh city | 6.2% |
| Đông Nam Bộ | 6.2% |
| Cà Mau | 6.1% |
| Son La | 5.9% |
| Hà Giang | 5.9% |
| Lâm Đồng | 5.8% |
| Điện Biên | 5.5% |
| Lai Chau | 5.5% |
| Đắk Lắk | 5.3% |
| Kon Tum | 5.1% |
| Gia Lai | 5.1% |
| Bình Phước | 4.9% |
| Lào Cai | 4.9% |
| Bình Dương | 4.7% |
| Đắk Nông | 3.8% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
義大利 (99)
義大利 65 歲以上人口占比最高的一級行政區是 Biella（29.9%），最低是 Caserta（19%）；全國未加權平均 25%（Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3，2023 年）。In 義大利, the admin-1 unit with the highest share of population aged 65+ is Biella at 29.9%, and the lowest is Caserta at 19%; the unweighted national figure is 25% (Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3, 2023).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Biella | 29.9% |
| Savona | 29.7% |
| Genova | 29% |
| Trieste | 28.7% |
| Ferrara | 28.7% |
完整列表Full list (99)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Biella | 29.9% |
| Savona | 29.7% |
| Genova | 29% |
| Trieste | 28.7% |
| Ferrara | 28.7% |
| Grosseto | 28.7% |
| Terni | 28.6% |
| Alessandria | 28.4% |
| Imperia | 28.3% |
| Massa-Carrara | 28.3% |
| Verbano-Cusio-Ossola | 28% |
| Vercelli | 27.8% |
| Belluno | 27.8% |
| Livorno | 27.8% |
| La Spezia | 27.7% |
| Rovigo | 27.6% |
| Udine | 27.4% |
| Isernia | 27.2% |
| Asti | 27% |
| Nuoro | 26.8% |
| Gorizia | 26.8% |
| Rieti | 26.8% |
| Siena | 26.6% |
| Ascoli Piceno | 26.6% |
| Lucca | 26.5% |
| Fermo | 26.5% |
| Arezzo | 26.3% |
| Campobasso | 26.2% |
| Macerata | 26.2% |
| Chieti | 26.1% |
| Pistoia | 26.1% |
| Perugia | 26.1% |
| L'Aquila | 26% |
| Ravenna | 25.9% |
| Firenze | 25.9% |
| Ancona | 25.9% |
| Lecce | 25.7% |
| Venezia | 25.7% |
| Viterbo | 25.5% |
| Potenza | 25.2% |
| Piacenza | 25.2% |
| Pavia | 25% |
| Cremona | 25% |
| Sassari | 25% |
| Forlì-Cesena | 25% |
| Pisa | 25% |
| Pesaro e Urbino | 25% |
| Frosinone | 25% |
| Sondrio | 24.9% |
| Cuneo | 24.8% |
| Lecco | 24.8% |
| Messina | 24.8% |
| Enna | 24.8% |
| Cagliari | 24.8% |
| Pordenone | 24.8% |
| Brindisi | 24.7% |
| Novara | 24.6% |
| Taranto | 24.6% |
| Bologna | 24.6% |
| Varese | 24.5% |
| Teramo | 24.5% |
| Pescara | 24.5% |
| Mantova | 24.3% |
| Matera | 24.3% |
| Trapani | 24.3% |
| Benevento | 24.2% |
| Catanzaro | 24.1% |
| Cosenza | 24% |
| Rimini | 24% |
| Como | 23.8% |
| Padova | 23.8% |
| Vibo Valentia | 23.7% |
| Agrigento | 23.7% |
| Modena | 23.5% |
| Avellino | 23.4% |
| Treviso | 23.4% |
| Parma | 23.3% |
| Bari | 23.2% |
| Reggio Calabria | 23.2% |
| Trento | 23.2% |
| Vicenza | 23.1% |
| Milano | 22.9% |
| Foggia | 22.9% |
| Siracusa | 22.9% |
| Verona | 22.9% |
| Caltanissetta | 22.8% |
| Prato | 22.7% |
| Roma | 22.7% |
| Brescia | 22.5% |
| Palermo | 22.5% |
| Latina | 22.5% |
| Lodi | 22.4% |
| Salerno | 22.3% |
| Bergamo | 22.1% |
| Catania | 21.5% |
| Ragusa | 21.3% |
| Barletta-Andria Trani | 21.1% |
| Napoli | 19.6% |
| Caserta | 19% |
來源：Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3（2023 年）Source: Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-3 (2023)
德國 (16)
德國 65 歲以上人口占比最高的一級行政區是 Sachsen-Anhalt（27.8%），最低是 Hamburg（18.1%）；全國未加權平均 23.2%（Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-1，2023 年）。In 德國, the admin-1 unit with the highest share of population aged 65+ is Sachsen-Anhalt at 27.8%, and the lowest is Hamburg at 18.1%; the unweighted national figure is 23.2% (Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-1, 2023).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Sachsen-Anhalt | 27.8% |
| Thüringen | 27.1% |
| Mecklenburg-Vorpommern | 27% |
| Sachsen | 26.7% |
| Brandenburg | 25.7% |
完整列表Full list (16)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Sachsen-Anhalt | 27.8% |
| Thüringen | 27.1% |
| Mecklenburg-Vorpommern | 27% |
| Sachsen | 26.7% |
| Brandenburg | 25.7% |
| Saarland | 24.6% |
| Schleswig-Holstein | 23.6% |
| Niedersachsen | 22.7% |
| Rheinland-Pfalz | 22.6% |
| Nordrhein-Westfalen | 21.6% |
| Hessen | 21.2% |
| Bayern | 21.1% |
| Baden-Württemberg | 20.9% |
| Bremen | 20.8% |
| Berlin | 19.2% |
| Hamburg | 18.1% |
來源：Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-1（2023 年）Source: Eurostat demo_r_pjanind3 (PC_Y65_MAX), NUTS-1 (2023)
緬甸 (14)
緬甸 65 歲以上人口占比最高的一級行政區是 Magway（7.9%），最低是 Kayah（4.3%）（WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)，2020 年）。In 緬甸, the admin-1 unit with the highest share of population aged 65+ is Magway at 7.9%, and the lowest is Kayah at 4.3% (WorldPop 2020 1km unconstrained age/sex (CC BY 4.0), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Magway | 7.9% |
| Rakhine | 7.4% |
| Mon | 7.2% |
| Bago | 7% |
| Sagaing | 6.9% |
完整列表Full list (14)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Magway | 7.9% |
| Rakhine | 7.4% |
| Mon | 7.2% |
| Bago | 7% |
| Sagaing | 6.9% |
| Mandalay | 6.9% |
| Ayeyarwady | 6.4% |
| Yangon | 6.3% |
| Kayin | 5.9% |
| Tanintharyi | 5.7% |
| Chin | 5.6% |
| Shan | 4.8% |
| Kachin | 4.5% |
| Kayah | 4.3% |
來源：WorldPop 2020 1km unconstrained age/sex (CC BY 4.0)（2020 年）Source: WorldPop 2020 1km unconstrained age/sex (CC BY 4.0) (2020)
墨西哥 (32)
墨西哥 65 歲以上人口占比最高的一級行政區是 Distrito Federal（11.1%），最低是 Quintana Roo（4.4%）；全國未加權平均 8%（INEGI Censo 2020 (población por entidad y edad)，2020 年）。In 墨西哥, the admin-1 unit with the highest share of population aged 65+ is Distrito Federal at 11.1%, and the lowest is Quintana Roo at 4.4%; the unweighted national figure is 8% (INEGI Censo 2020 (población por entidad y edad), 2020).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Distrito Federal | 11.1% |
| Veracruz | 10% |
| Morelos | 9.6% |
| Oaxaca | 9.6% |
| San Luis Potosí | 9% |
完整列表Full list (32)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Distrito Federal | 11.1% |
| Veracruz | 10% |
| Morelos | 9.6% |
| Oaxaca | 9.6% |
| San Luis Potosí | 9% |
| Guerrero | 8.9% |
| Michoacán | 8.9% |
| Nayarit | 8.9% |
| Sinaloa | 8.9% |
| Yucatán | 8.7% |
| Zacatecas | 8.7% |
| Hidalgo | 8.6% |
| Colima | 8.4% |
| Jalisco | 8.2% |
| Tamaulipas | 8.1% |
| Sonora | 8% |
| Durango | 7.8% |
| Puebla | 7.8% |
| Guanajuato | 7.6% |
| Nuevo León | 7.6% |
| Campeche | 7.5% |
| Chihuahua | 7.5% |
| México | 7.4% |
| Tlaxcala | 7.4% |
| Coahuila | 7.3% |
| Tabasco | 7.2% |
| Aguascalientes | 6.8% |
| Querétaro | 6.7% |
| Baja California | 6.5% |
| Chiapas | 6.3% |
| Baja California Sur | 6.1% |
| Quintana Roo | 4.4% |
來源：INEGI Censo 2020 (población por entidad y edad)（2020 年）Source: INEGI Censo 2020 (población por entidad y edad) (2020)
澳洲 (8)
澳洲 65 歲以上人口占比最高的一級行政區是 Tasmania（21.8%），最低是 Northern Territory（9.6%）；全國未加權平均 16.7%（ABS ERP by age, state (ERP_ASGS2021)，2024 年）。In 澳洲, the admin-1 unit with the highest share of population aged 65+ is Tasmania at 21.8%, and the lowest is Northern Territory at 9.6%; the unweighted national figure is 16.7% (ABS ERP by age, state (ERP_ASGS2021), 2024).
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Tasmania | 21.8% |
| South Australia | 20.3% |
| New South Wales | 17.7% |
| Queensland | 17.2% |
| Victoria | 16.7% |
完整列表Full list (8)
| 行政區Unit | 65 歲以上占比Share aged 65+ |
|---|---|
| Tasmania | 21.8% |
| South Australia | 20.3% |
| New South Wales | 17.7% |
| Queensland | 17.2% |
| Victoria | 16.7% |
| Western Australia | 16.2% |
| Australian Capital Territory | 13.9% |
| Northern Territory | 9.6% |
來源：ABS ERP by age, state (ERP_ASGS2021)（2024 年）Source: ABS ERP by age, state (ERP_ASGS2021) (2024)
資料來源與參考文獻Sources & references
本工具整合以下公開文獻、政府與國際組織資料庫。所有失智盛行率與腦齡數字皆為教育性模型估計，非醫療診斷。This tool builds on the public literature, government, and international datasets below. All dementia-prevalence and brain-age figures are educational modelled estimates, not medical diagnoses.
※ 資料庫類來源（GBD、內政部戶政司 #77132、日本 e-Stat、韓國 KOSIS、ACAG）均於 2026-07-14 存取；各條標註所用資料年份。※ Database sources (GBD, MOI #77132, Japan e-Stat, Korea KOSIS, ACAG) were accessed 2026-07-14; each entry notes the data year used.
① 失智風險與腦齡模型① Dementia risk & brain-age model
- Livingston G, et al. Dementia prevention, intervention, and care: 2024 report of the Lancet standing Commission. Lancet 2024;404:572–628. doi:10.1016/S0140-6736(24)01296-0
- Moguilner S, Ibáñez A, et al. Brain clocks capture diversity and disparities in aging and dementia. Nat Med 2024;30:3646–57. doi:10.1038/s41591-024-03209-x
- Long-term air pollution exposure and incident dementia: a systematic review and meta-analysis. Lancet Planet Health 2025 (≈ HR 1.08 per 5 µg/m³ PM2.5). doi:10.1016/S2542-5196(25)00118-4
- Ziegler-Graham K, et al. Worldwide variation in the doubling time of Alzheimer's disease incidence rates (≈ 5.5 years). Alzheimers Dement 2008;4:316–23. doi:10.1016/j.jalz.2008.05.2479
② 失智盛行率調查與資料庫② Dementia-prevalence surveys & databases
- 台灣：國家衛生研究院（NHRI）112年(2023)全國社區失智症流行病學調查（年齡別盛行率）；年齡別盛行率方法參 Sun Y, et al. PLoS ONE 2014。Taiwan: NHRI 2023 nationwide community dementia survey (age-band prevalence); method per Sun Y, et al. PLoS ONE 2014. NHRI · doi:10.1371/journal.pone.0100303
- 美／巴／墨（州級）與日／韓（全國費率）失智盛行率之骨幹：Rate backbone for US/BR/MX (sub-national) and JP/KR (national rates): IHME Global Burden of Disease GBD 2023 — Alzheimer's disease & other dementias, prevalence（資料年份 2023data year 2023）. vizhub.healthdata.org/gbd-results
- 中國：China: Jia L, et al. Prevalence of dementia in China (CCAS). Lancet Public Health 2020. doi:10.1016/S2468-2667(20)30185-7 · Liu, Gao, et al. Geographical variation in dementia prevalence across China (per-province). Lancet Reg Health – West Pac 2024. PMC11225804
- 印度：India: Lee J, et al. Prevalence of dementia in India: national and state estimates (LASI-DAD). Alzheimer's & Dementia 2023. doi:10.1002/alz.12928
- 日本：Japan: Ninomiya T, et al. 久山町研究（37 年趨勢，年齡別盛行率）Hisayama Study (37-year trends, age-specific prevalence). Alzheimer's Research & Therapy 2025. doi:10.1186/s13195-025-01909-1 · 厚生労働省 全國認知症・MCI 高齡者推計（Ninomiya 研究班，2024）MHLW nationwide dementia & MCI estimates (Ninomiya group, 2024) mhlw.go.jp
- 韓國：Korea: 중앙치매센터 國立失智症中心《大韓民國失智現況》（年齡別유병률・MCI）National Institute of Dementia — Korean Dementia Observatory (age-specific prevalence & MCI) nid.or.kr
- MCI（輕度認知障礙）圖層 — 底色為區域統合估計：Bai et al. 2022《Age & Ageing》依世界銀行區域的 MCI 盛行率（50 歲以上、社區）。約 70 國以其全國研究值覆寫底色（限合理範圍 3–40%，超出者多為 MoCA 篩檢高估、退回區域值），例：台灣 Sun 2014/2017、日本 MHLW 2024、南韓 KDO 2020、印度 LASI-DAD、中國 Xue 2021；逐國來源見 scripts/mci-scd-sources.json。定義／年齡層不一，不可跨國比較，為模型估計。MCI (mild cognitive impairment) layer — baseline is a regional pooled estimate: Bai et al. 2022 (Age & Ageing), MCI prevalence by World Bank region (adults 50+, community). ~70 countries overwrite the baseline with a national-study value (plausible 3–40%; higher MoCA screening figures revert to regional), e.g. Taiwan Sun 2014/2017, Japan MHLW 2024, Korea KDO 2020, India LASI-DAD, China Xue 2021; per-country sources in scripts/mci-scd-sources.json. Definitions/age bands vary — not comparable, a modelled estimate. Bai 2022 · MHLW
- MCI 佐證：多篇全球統合估計一致支持上列區域底色 — Song 2023 全球 19.7%、Salari 2025 老年族群 23.7%、拉丁美洲專屬統合 14.95%（2021）、中國 Lu 2021 12.2% / Xue 2021 15.4%（差異源於年齡切點與量表）。SCD（主觀認知衰退）已上獨立「SCD（自述）」圖層（38 國，多為單題自述、各自尺度、不可跨國比較，7–76%）；仍無全球統合可當底色，逐國來源見 scripts/mci-scd-sources.json。MCI corroboration: several global meta-analyses agree with the regional baseline above — Song 2023 global 19.7%, Salari 2025 geriatric 23.7%, Latin America pooled 14.95% (2021), China Lu 2021 12.2% / Xue 2021 15.4% (differences reflect age cut-off and instrument). SCD (subjective cognitive decline) now has its own layer (38 countries, mostly single-item self-report, own scale, not comparable, 7–76%); still no global meta as a baseline; per-country sources in scripts/mci-scd-sources.json. Song 2023 · Salari 2025
③ 空氣污染（PM2.5）③ Air pollution (PM2.5)
- Atmospheric Composition Analysis Group (ACAG), Washington University in St. Louis — surface PM2.5 V6.GL.03 (satellite-derived, annual 1998–2024), CC BY 4.0. Methods: van Donkelaar A, et al. Environ Sci Technol 2021 (doi:10.1021/acs.est.1c05309); Shen S, et al. ACS ES&T Air 2024 (doi:10.1021/acsestair.3c00054). dataset
- WHO 全球空氣品質指引 2021（年均 PM2.5 建議 ≤ 5 µg/m³）。WHO Global Air Quality Guidelines 2021 (recommended annual PM2.5 ≤ 5 µg/m³). who.int
④ 地理界線④ Administrative boundaries
- 台灣：內政部國土測繪中心（NLSC）鄉鎮市區界線，經 taiwan-atlas 轉製（OGDL-Taiwan-1.0）。Taiwan: township boundaries from the National Land Surveying and Mapping Center (NLSC), via taiwan-atlas (OGDL-Taiwan-1.0). data.gov.tw/7441
- 其他國家：Other countries: Natural Earth admin-1 boundaries (public domain). naturalearthdata.com
⑤ 人口與國際報告⑤ Population & international reports
- 台灣人口：內政部戶政司 #77132 鄉鎮市區單一年齡人口（資料月份 2026-06）。Taiwan population: MOI #77132 township single-year-age population (data 2026-06). data.gov.tw/77132
- 日本人口：總務省統計局 e-Stat 都道府県・年齡別人口（資料 2024）。韓國人口：統計廳 KOSIS 시도・연령별 인구（資料 2026）。Japan population: Statistics Bureau e-Stat, prefecture × age (data 2024). Korea population: Statistics Korea KOSIS, Si-do × age (data 2026). e-stat.go.jp · kosis.kr
- 各國 admin-1「65 歲以上人口占比」官方統計（2026-08 起接入，取代先前的 WorldPop 估計；完整逐國來源、資料年份與 API 端點見 Each country's admin-1 share aged 65+ — official statistics (wired in from 2026-08, superseding the earlier WorldPop estimate; full per-country source, data year & API endpoint in aging-sources.json）：歐盟德法義西波 )：EU DE/FR/IT/ES/PL Eurostat、英國 UK ONS·Nomis、美國 US Census ACS、加拿大 Canada StatCan、澳洲 Australia ABS、巴西 Brazil IBGE、墨西哥 Mexico INEGI、紐西蘭 NZ Stats NZ、中國 2020 普查 China 2020 census 國家統計局、印度 2011 普查 C-14 India 2011 census C-14 censusindia.gov.in、伊朗 2016 普查（經 Iran 2016 census (via UN OCHA·HDX）、土耳其 )、Türkiye TÜİK ADNKS 2024。存取日 2026-08–09。. Accessed 2026-08–09.
- 失智盛行率的 admin-1 人口分母，以及東南亞七國（泰、越、印尼、菲、馬、緬、孟）高齡層的 admin-1 來源：WorldPop 2020 1km 年齡／性別網格（資料 2020，CC BY 4.0）；UN World Population Prospects 為國家別校準。部分高所得國家 WorldPop 年齡結構在區間近乎一致，故以全國估計值呈現。Admin-1 population denominator for dementia prevalence, and the admin-1 aging source for seven SE/South-Asian countries (TH, VN, ID, PH, MY, MM, BD): WorldPop 2020 1km age/sex grids (data 2020, CC BY 4.0); UN World Population Prospects for national calibration. For some high-income countries WorldPop's age structure is near-uniform across areas, so a single national estimate is shown. worldpop.org · population.un.org/wpp
- WHO. 失智症全球公共衛生應對現況報告，2021（全球失智人口 55M → 78M（2030）→ 139M（2050））。Global status report on the public health response to dementia, 2021 (55M now → 78M by 2030 → 139M by 2050). who.int
- 高齡化社會分級標準（高齡化 ≥7%、高齡 ≥14%、超高齡 ≥20%，以 65 歲以上人口占比計）：聯合國經濟社會事務部《World Population Ageing》；7% 門檻源自 UN 1956《The Aging of Populations and Its Economic and Social Implications》Population Studies No. 26。全球高齡人口占比採 World Bank SP.POP.65UP.TO.ZS（2025，存取 2026-07-16）；台灣不在該庫，改採內政部戶政司 2025 年底 20.06%。Aging-society tiers (aging ≥7%, aged ≥14%, super-aged ≥20%, by share of population aged 65+): UN DESA, World Population Ageing; the 7% threshold originates in UN (1956), The Aging of Populations and Its Economic and Social Implications, Population Studies No. 26. Global 65+ shares use World Bank SP.POP.65UP.TO.ZS (2025, accessed 2026-07-16); Taiwan, excluded from that database, uses MOI 2025 year-end (20.06%). un.org/ageing · data.worldbank.org
⑥ 可調控風險因子與 PAF（風險圖層）⑥ Modifiable risk factors & PAF (risk layers)
- 相對風險（RR）與可歸因比例（PAF）架構取自 Livingston 2024 Lancet 委員會（見 ①）。PAF = P(RR−1)/[1+P(RR−1)]；5 因子合併採 1−Π(1−PAF)（假設獨立），為下限估計。Relative risks (RR) and the population-attributable-fraction (PAF) framework are from the Livingston 2024 Lancet Commission (see ①). PAF = P(RR−1)/[1+P(RR−1)]; the 5 factors are combined via 1−Π(1−PAF) (independence-assumed), a floor estimate.
- 高血壓／糖尿病／肥胖（全球各國、全成人、年齡標準化、實測，含台灣）：Hypertension / diabetes / obesity (all countries, adult, age-standardised, measured; incl. Taiwan): NCD Risk Factor Collaboration (NCD-RisC) — Lancet 2017;389:37–55 doi（血壓，資料 2015BP, data 2015）· Lancet 2024;404:2077–93 doi（糖尿病，資料 2022diabetes, data 2022）· Nature 2026（BMI≥30，資料 2024data 2024）ncdrisc.org
- 吸菸與身體活動不足（全球各國，台灣除外見下；年齡標準化，吸菸資料至 2025、身體活動至 2022，存取日 2026-07-16）：Smoking & insufficient physical activity (all countries except Taiwan, see below; age-standardised, smoking to 2025, activity to 2022, accessed 2026-07-16): WHO Global Health Observatory（指標indicators M_Est_tob_curr, NCD_PAC）. who.int/data/gho
- 台灣吸菸與身體活動不足：2021 年國民健康訪問調查（衛福部國民健康署）。WHO GHO 不含台灣，故由此填補；台灣高血壓／糖尿病／肥胖仍採 NCD-RisC 台灣值以與各國可比。Taiwan smoking & inactivity: 2021 National Health Interview Survey (Taiwan Health Promotion Administration). WHO GHO has no Taiwan row, so these fill it; Taiwan's hypertension/diabetes/obesity use NCD-RisC for cross-country comparability. hpa.gov.tw
⑦ 縮寫對照⑦ Abbreviations
- PAF — 可歸因比例（population attributable fraction）——某危險因子若消除，理論上可減少的失智比例population attributable fraction — the share of dementia that could, in theory, be avoided if a risk factor were removed
- RR — 相對風險（relative risk）relative risk
- PM2.5 — 細懸浮微粒（fine particulate matter，粒徑 ≤2.5 µm）fine particulate matter (aerodynamic diameter ≤2.5 µm)
- MCI — 輕度認知障礙（mild cognitive impairment）mild cognitive impairment
- SCD — 主觀認知衰退（subjective cognitive decline）subjective cognitive decline
- GBD — 全球疾病負擔研究（Global Burden of Disease study，IHME）Global Burden of Disease study (IHME)
- NCD-RisC — 非傳染病危險因子合作組織（NCD Risk Factor Collaboration）NCD Risk Factor Collaboration
- WHO — 世界衛生組織（World Health Organization）；GHO 為其全球衛生觀測站World Health Organization; GHO is its Global Health Observatory
- AAIC — 阿茲海默症協會國際年會（Alzheimer's Association International Conference）Alzheimer's Association International Conference
- ACAG — 大氣成分分析組（Atmospheric Composition Analysis Group，衛星 PM2.5 資料來源）Atmospheric Composition Analysis Group (satellite PM2.5 data source)
- exposome — 環境暴露總和：一生累積的環境暴露總和the exposome: the sum of one's lifetime environmental exposures
⑧ 資料授權⑧ Data licence
- 本站彙編與衍生的資料採 The datasets this project compiles and derives are licensed CC BY 4.0。姓名標示請寫：Brain Exposome — brain-exposome.mattye.dev. Please attribute as: Brain Exposome — brain-exposome.mattye.dev
- 例外——失智盛行率圖層Exception — the dementia-prevalence layer：該層衍生自 GBD 2023（IHME），其協議為「非商業＋姓名標示」。CC BY 4.0 允許商業再利用，本站無從轉授這項權利，因此該圖層僅供非商業使用，且須同時標註 Global Burden of Disease Study 2023 (GBD 2023), IHME。it derives from GBD 2023 (IHME), released under a free-of-charge non-commercial + attribution agreement. CC BY 4.0 permits commercial reuse and this project cannot pass that right on, so the dementia layer is for non-commercial use only and must also credit the Global Burden of Disease Study 2023 (GBD 2023), IHME. IHME 使用協議IHME agreement
- 上游來源各自保留其原有條款（見上方 ①–⑥ 各條，以及每筆資料的 source 欄）。本站只發布衍生的各行政區數值，不重新散布原始檔案。Upstream sources keep their own terms (see ①–⑥ above and each record's source field). Only derived per-unit values are published here; raw source files are not redistributed.