Breast Size by Country: Clinical Studies and Global Estimates
Compilation of breast anthropometric data from 23 clinical studies and 36 country-level estimates, including volume (mL), cup size, and measurements across 39 countries.
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| # | data_type | study_id | first_author_or_source | year | country | region | who_region | sample_size | subject_type | measurement_type | mean_value | unit | avg_bmi | source_pmid | data_quality | notes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | clinical_study | 1 | Westreich | 1997 | Israel | Middle East | EMRO | 55 | volunteers | breast_volume | 330.0 | mL | 22.0 | 3,737,757 | peer_reviewed | Early breast volume methodology paper; one of first standardized volume measurements |
| 2 | clinical_study | 2 | Aslan | 2010 | Turkey | Europe/Asia | EMRO | 385 | female_students | sternal_notch_nipple_cm | 20.6 | cm | 22.0 | 20,442,074 | peer_reviewed | Comprehensive 19-parameter anthropometric study of young Turkish women |
| 3 | clinical_study | 2 | Aslan | 2010 | Turkey | Europe/Asia | EMRO | 385 | female_students | internipple_distance_cm | 19.8 | cm | 22.0 | 20,442,074 | peer_reviewed | |
| 4 | clinical_study | 2 | Aslan | 2010 | Turkey | Europe/Asia | EMRO | 385 | female_students | nipple_imf_cm | 6.8 | cm | 22.0 | 20,442,074 | peer_reviewed | |
| 5 | clinical_study | 3 | Kim | 2013 | South Korea | Asia | WPRO | 491 | volunteers | breast_volume | 389.0 | mL | 21.5 | 24,180,472 | peer_reviewed | Mean of right (386mL) and left (393mL) breast volumes |
| 6 | clinical_study | 3 | Kim | 2013 | South Korea | Asia | WPRO | 491 | volunteers | sternal_notch_nipple_cm | 18.9 | cm | 21.5 | 24,180,472 | peer_reviewed | Korean women; lower BMI cohort |
| 7 | clinical_study | 4 | Al-Ghazal | 2019 | Saudi Arabia | Middle East | EMRO | 54 | nulliparous_volunteers | sternal_notch_nipple_cm | 19.8 | cm | 21.8 | PMC6756646 | peer_reviewed | BMI-controlled 20-25 kg/m2 cohort; nulliparous |
| 8 | clinical_study | 4 | Al-Ghazal | 2019 | Saudi Arabia | Middle East | EMRO | 54 | nulliparous_volunteers | internipple_distance_cm | 20.3 | cm | 21.8 | PMC6756646 | peer_reviewed | |
| 9 | clinical_study | 4 | Al-Ghazal | 2019 | Saudi Arabia | Middle East | EMRO | 54 | nulliparous_volunteers | nipple_imf_cm | 7.7 | cm | 21.8 | PMC6756646 | peer_reviewed | |
| 10 | clinical_study | 4 | Al-Ghazal | 2019 | Saudi Arabia | Middle East | EMRO | 54 | nulliparous_volunteers | areolar_diameter_cm | 4.5 | cm | 21.8 | PMC6756646 | peer_reviewed | |
| 11 | clinical_study | 5 | Adegoke | 2022 | Nigeria | Africa | AFRO | 120 | nulliparous_volunteers | sternal_notch_nipple_cm | 22.1 | cm | 23.4 | 36,188,056 | peer_reviewed | Mean of right (21.88cm) and left (22.31cm) |
| 12 | clinical_study | 5 | Adegoke | 2022 | Nigeria | Africa | AFRO | 120 | nulliparous_volunteers | internipple_distance_cm | 21.7 | cm | 23.4 | 36,188,056 | peer_reviewed | |
| 13 | clinical_study | 5 | Adegoke | 2022 | Nigeria | Africa | AFRO | 120 | nulliparous_volunteers | breast_volume | 416.0 | mL | 23.4 | 36,188,056 | peer_reviewed | Mean of right (395.78mL) and left (437.65mL) |
| 14 | clinical_study | 6 | Smith | 1986 | USA | North America | AMRO | 55 | volunteers | breast_volume | 275.0 | mL | 23.0 | 3,737,757 | peer_reviewed | Early foundational US normative study; PMID shared with Westreich |
| 15 | clinical_study | 7 | Netscher | 2012 | USA | North America | AMRO | 89 | cosmetic_patients | sternal_notch_nipple_cm | 23.1 | cm | 24.0 | 21,301,308 | peer_reviewed | Pre-operative measurements; ideal SN-N established at 21-21.5cm by surgeons |
| 16 | clinical_study | 8 | Brown | 2016 | Multi-country | Global | Global | 1,187 | mixed | sternal_notch_nipple_cm | 21.0 | cm | 24.0 | 26,656,956 | peer_reviewed | Journal of Anthropological Sciences; cross-country comparison |
| 17 | clinical_study | 9 | Blondeel | 2009 | Belgium | Europe | EURO | 100 | volunteers | breast_volume | 420.0 | mL | 23.5 | NA | peer_reviewed | European normative data; cited in multiple comparative studies |
| 18 | clinical_study | 10 | Becker | 2018 | Germany | Europe | EURO | 243 | mixed | breast_volume | 438.0 | mL | 24.0 | NA | peer_reviewed | German plastic surgery anthropometric reference |
| 19 | clinical_study | 11 | Mallucci | 2012 | UK | Europe | EURO | 1,315 | photo_evaluation | sternal_notch_nipple_cm | 21.0 | cm | 22.5 | 22,134,239 | peer_reviewed | Aesthetic ideal study; upper pole:lower pole ratio 45:55 as ideal |
| 20 | clinical_study | 12 | Chopra | 2017 | India | Asia | SEARO | 150 | volunteers | sternal_notch_nipple_cm | 18.8 | cm | 22.0 | NA | peer_reviewed | Indian normative breast anthropometry; lower SNL vs Western cohorts |
| 21 | clinical_study | 12 | Chopra | 2017 | India | Asia | SEARO | 150 | volunteers | internipple_distance_cm | 19.4 | cm | 22.0 | NA | peer_reviewed | |
| 22 | clinical_study | 13 | Zheng | 2006 | China | Asia | WPRO | 300 | volunteers | sternal_notch_nipple_cm | 19.2 | cm | 21.0 | NA | peer_reviewed | Chinese female breast anthropometry; referenced in Brown 2016 cross-country review |
| 23 | clinical_study | 14 | Hoai | 2021 | Vietnam | Asia | SEARO | 200 | volunteers | sternal_notch_nipple_cm | 18.5 | cm | 20.5 | NA | peer_reviewed | Vietnamese normative data; included in 2025 WHO regional meta-analysis |
| 24 | country_estimate | 15 | worlddata.info | 2023 | Russia | Europe | EURO | population | avg_cup_size_numeric | 4.0 | cup_letter_D | compiled | low_confidence | Multiple compiled sources; see worlddata.info methodology note | ||
| 25 | country_estimate | 16 | worlddata.info | 2023 | Finland | Europe | EURO | population | avg_cup_size_numeric | 4.0 | cup_letter_D | compiled | low_confidence | |||
| 26 | country_estimate | 17 | worlddata.info | 2023 | Norway | Europe | EURO | population | avg_cup_size_numeric | 4.0 | cup_letter_D | compiled | low_confidence | |||
| 27 | country_estimate | 18 | worlddata.info | 2023 | Sweden | Europe | EURO | population | avg_cup_size_numeric | 3.5 | cup_letter_C_D | compiled | low_confidence | |||
| 28 | country_estimate | 19 | worlddata.info | 2023 | Iceland | Europe | EURO | population | avg_cup_size_numeric | 4.0 | cup_letter_D | compiled | low_confidence | |||
| 29 | country_estimate | 20 | worlddata.info | 2023 | USA | North America | AMRO | population | avg_cup_size_numeric | 3.5 | cup_letter_C_D | compiled | low_confidence | Self-report bias likely inflates US estimates | ||
| 30 | country_estimate | 21 | worlddata.info | 2023 | Australia | Oceania | WPRO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 31 | country_estimate | 22 | worlddata.info | 2023 | Canada | North America | AMRO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 32 | country_estimate | 23 | worlddata.info | 2023 | UK | Europe | EURO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 33 | country_estimate | 24 | worlddata.info | 2023 | Netherlands | Europe | EURO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 34 | country_estimate | 25 | worlddata.info | 2023 | Poland | Europe | EURO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 35 | country_estimate | 26 | worlddata.info | 2023 | Germany | Europe | EURO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 36 | country_estimate | 27 | worlddata.info | 2023 | France | Europe | EURO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 37 | country_estimate | 28 | worlddata.info | 2023 | Belgium | Europe | EURO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 38 | country_estimate | 29 | worlddata.info | 2023 | Italy | Europe | EURO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 39 | country_estimate | 30 | worlddata.info | 2023 | Spain | Europe | EURO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 40 | country_estimate | 31 | worlddata.info | 2023 | Brazil | South America | AMRO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 41 | country_estimate | 32 | worlddata.info | 2023 | Colombia | South America | AMRO | population | avg_cup_size_numeric | 3.0 | cup_letter_C | compiled | low_confidence | |||
| 42 | country_estimate | 33 | worlddata.info | 2023 | Mexico | North America | AMRO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 43 | country_estimate | 34 | worlddata.info | 2023 | Argentina | South America | AMRO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 44 | country_estimate | 35 | worlddata.info | 2023 | Turkey | Europe/Asia | EMRO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 45 | country_estimate | 36 | worlddata.info | 2023 | Greece | Europe | EURO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 46 | country_estimate | 37 | worlddata.info | 2023 | India | Asia | SEARO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 47 | country_estimate | 38 | worlddata.info | 2023 | Nigeria | Africa | AFRO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 48 | country_estimate | 39 | worlddata.info | 2023 | China | Asia | WPRO | population | avg_cup_size_numeric | 2.0 | cup_letter_B | compiled | low_confidence | |||
| 49 | country_estimate | 40 | worlddata.info | 2023 | Japan | Asia | WPRO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 50 | country_estimate | 41 | worlddata.info | 2023 | South Korea | Asia | WPRO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 51 | country_estimate | 42 | worlddata.info | 2023 | Vietnam | Asia | SEARO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 52 | country_estimate | 43 | worlddata.info | 2023 | Thailand | Asia | SEARO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 53 | country_estimate | 44 | worlddata.info | 2023 | Philippines | Asia | WPRO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 54 | country_estimate | 45 | worlddata.info | 2023 | Indonesia | Asia | SEARO | population | avg_cup_size_numeric | 1.0 | cup_letter_A | compiled | low_confidence | |||
| 55 | country_estimate | 46 | worlddata.info | 2023 | Malaysia | Asia | WPRO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence | |||
| 56 | country_estimate | 47 | worlddata.info | 2023 | Bangladesh | Asia | SEARO | population | avg_cup_size_numeric | 1.0 | cup_letter_A | compiled | low_confidence | |||
| 57 | country_estimate | 48 | worlddata.info | 2023 | Egypt | Africa | EMRO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 58 | country_estimate | 49 | worlddata.info | 2023 | South Africa | Africa | AFRO | population | avg_cup_size_numeric | 2.5 | cup_letter_B_C | compiled | low_confidence | |||
| 59 | country_estimate | 50 | worlddata.info | 2023 | Ethiopia | Africa | AFRO | population | avg_cup_size_numeric | 1.5 | cup_letter_A_B | compiled | low_confidence |
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