Search
Close
Search
Advanced Search
Search Menu
AI Discovery Assistant

Abstract

Breast cancer is the most common neoplasm in the world among women. The age-specific incidences and onset ages vary widely between Asian and Western countries/regions. Invasive breast cancer cases among women from 1997 to 2011 were abstracted from the International Agency for Research on Cancer and the Taiwan Cancer Registry. Age-period-cohort analysis was performed to examine the trends. The cohort effect was prominent in South Korea, Taiwan, Japan, and Thailand, possibly related to the timing of westernization. The risk of breast cancer initially rose with the birth cohorts in Hong Kong and India (both former British colonies), peaked, and then declined in recent birth cohorts. Unlike other Asian countries/regions, virtually no birth cohort effect was identified in the Philippines (a Spanish colony in 1565 and the first Asian country to adopt Western cultural aspects). Moreover, an at-most negligible birth cohort effect was identified for all ethnic groups (including Asian immigrants) in the United States. This global study identified birth cohort effects in most Asian countries/regions but virtually no impact in Western countries/regions. The timing of westernization was associated with the birth cohort effect.

birth cohort effect, breast cancer, global study, westernization

Abbreviations

     
  • APC

    age-period-cohort

    •  
  • ER

    estrogen receptor

    •  
  • NPCR

    National Program of Cancer Registries

    •  
  • SEER

    Surveillance, Epidemiology, and End Results Program

Breast cancer has overtaken lung cancer as the most common cancer globally (1), with approximately 2.1 million new cases in 2018 (2). The incidence rates of breast cancer are increasing monotonically with age in Western countries (3). By contrast, breast cancer occurs in Asian women at a younger age, with the incidence rate peaking before age 50 years (4). This dissimilarity suggests the possibility of racial or geographical variations in breast cancer (5, 6).

Most research on the age-specific incidence of breast cancer has entailed cross-sectional analysis. However, some authors have proposed that among Asian women, this incidence is related to birth cohort effects (7–10). A birth cohort represents a group of people born at the same time who may share similar lifestyles and environmental exposures. Global comparisons by area and period may provide clues to the causes of disease and the effects of interventions and serve as indicators for preventive strategies. However, to our knowledge, no global study has compared birth cohort effects in breast cancer.

This study investigated global breast cancer incidence trends between 1997 and 2011 using age-period-cohort (APC) analysis and evaluated birth cohort effects for breast cancer.

METHODS

Data source

Invasive breast cancer cases among women (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, code C50) and corresponding populations at risk were abstracted from the International Agency for Research on Cancer: Cancer Incidence in Five Continents and the Taiwan Cancer Registry; the data, obtained from a comprehensive and quality-assured population-based cancer registry database (updated to 2012) (11–13), included summary information from the registry on ethnicity, cancer site, sex, and 5-year age group classifications for patients in 47 countries. Incidence rates for Black and White persons from the data of the US Surveillance, Epidemiology, and End Results Program (SEER) were examined separately. Data from the US National Program of Cancer Registries (NPCR) extracted incidence rates for White, Black, Asian/Pacific Islander, and Native American persons separately. Data from Los Angeles, California (United States), were categorized into Black, Hispanic White, non-Hispanic White, Japanese, Chinese, South Korean, and Filipino. Overall, data were obtained from 57 countries/regions.

Data from patients younger than 25 years were excluded from the study because of the scarcity of such cases. The (truncated) world standard (World Health Organization, 2000) population proportions (age groups: 25–29, 30–34, …, 70–74, and over 75) were used to calculate age-standardized incidence rates.

Trend analysis using joinpoint models

We applied the joinpoint regression model developed by Kim et al. (14) to partition the age-standardized incidence trend of the entire study period into different trends for different time sections using nodes selected by the model. We calculated the average annual percent changes for different time sections to examine changes in age-standardized incidence rates over time. To assess the magnitude and direction of the recent trend in each country/region, we used the average annual percent changes over the 10 most recent years available (depending on the country/region).

Age-period-cohort models

Classical APC models separate an overall trend into age effects, reflecting risk variations across the human lifespan; period effects, representing environmental effects on all age groups; and cohort effects, capturing differential risk across birth cohorts. Because of the collinearity between the 3 factors (cohort = period − age), APC models suffer from a nonidentification problem. Here, we used the method proposed by Rosenberg et al. (15), which focuses on estimable parameters without attempting to separate the 3 effects. Estimable parameters include the following: net drift (the log-linear trend attributable to period and cohort effects and analogous to the average annual percent change over time); cross-sectional age curve (the age-specific rate in the reference cohort); longitudinal age curve (the fitted longitudinal age-specific rate in the reference cohort adjusted for period deviations); and cohort relative risk (the relative risk adjusted for age and nonlinear period effects in a cohort versus the reference cohort).

Input data included cases and population numbers for 3 periods (5-year periods of 1997–2001, 2002–2006, and 2007–2011) and 11 age groups (per 5 years: 25–29, 30–34, …, 70–74, and ≥75). Cohorts were obtained from 1920 to 1984. Patients born from 1920 to 1924 were defined as the 1922 cohort, those born from 1925 to 1929, the 1927 cohort, and so on. Cohort effects were presented as rate ratios, calculated as each cohort relative to the reference cohort, and adjusted for age and nonlinear period effects. The reference cohort was set to 1950–1954 (the 1952 cohort)—the middle cohort of the 13 cohorts.

Data management and analyses were performed using SAS (version 9.4; SAS Institute, Cary, North Carolina). Joinpoint models were examined using the software provided by the Surveillance Research Program of the National Cancer Institute of the United States (version 4.7.0.0) (14). The APC model was analyzed using the APC web tool (15, 16). Figures were plotted using ggplot2 in R (version 3.6.1; R Foundation for Statistical Computing, Vienna, Austria). All tests of statistical significance were 2-sided, and a P value of <0.05 was considered statistically significant.

RESULTS

Secular trend

Table 1 presents the average annual percent changes in age-standardized incidence rates for different time sections. Web Figure 1 (available at https://doi.org/10.1093/aje/kwac116) shows the age-standardized incidence rate trends over time. Three patterns of incidence rates were identified. The first pattern was an initially rising trend, which subsequently declined or stayed flat. This pattern occurred mainly in Western countries/regions (Canada, SEER data for White persons, Colombia, Brazil, India, Israel, Bulgaria, Croatia, Czech Republic, Denmark, France, Italy, the Netherlands, Norway, Slovenia, Spain, the United Kingdom, Australia, and New Zealand). The second pattern maintained a rising trend (Uganda, NPCR data for Black persons, Ecuador, Japan, South Korea, Taiwan, China, Hong Kong, Thailand, Turkey, Kuwait, Belarus, Cyprus, Estonia, Germany, Iceland, Ireland, Lithuania, Malta, Poland, Slovakia, and Switzerland). The third pattern was a flat line without noticeable changes (NPCR data for White persons, SEER data for Black persons, Costa Rica, Chile, Bahrain, the Philippines, and Austria).

Table 1
Open in new tab

Trends in Age-Standardized Incidence Rates of Breast Cancer, Multiple Countries, 1973–2012

Trend 1Trend 2Trend 3Trend 4Most Recent Available 10 Years
Region and PopulationPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPC95% CI
Africa
Ugandaa1993–20123.1b2003–20123.11.7, 4.4b
Americas
Canada1983–19911.9b1991–2012−0.12003–2012−0.1−0.3, 0.1
United States (NPCR, Black)1998–20120.3b2003–20120.30.1, 0.5b
United States (NPCR, White)1998–20010.02001–2004−3.32004–2012−0.22003–2012−0.6−1.2, 0.0b
United States (SEER, White)1978–19872.9b1987–20010.5b2001–2004−3.62004–2012−0.12003–2012−0.5−1.2, 0.3
United States (SEER, Black)1978–19883.11988–20120.22003–20120.20.0, 0.4b
Ecuadora1985–20121.8b2003–20121.81.3, 2.4b
Costa Rica1982–1987−3.3b1987–2000−3.6b2000–20111.4b2002–20111.40.3, 2.4b
Colombiaa1983–19961.3b1996–20017.02001–2012−1.6b2003–2012−1.6−3.0, −0.2b
Chilea1998–20120.82003–20120.8−1.0, 2.5
Brazila1993–20043.3b2003–2012−3.1b2003–2012−2.4−4.1, −0.7
Asia
Japana1973–19806.5b1980–19893.5b1989–1992−0.71992–20123.9b2003–20123.93.6, 4.2b
South Korea1993–1995−4.61995–20125.7b2003–20125.75.3, 6.1b
Taiwan1997–20124.8b2003–20124.84.4, 5.2b
Chinaa1988–19980.81998–20017.02001–20121.3b2003–20121.30.3, 2.3b
Hong Kong1983–19930.8b1993–20122.3b2003–20122.32.0, 2.6b
Bahrain1998–20120.72003–20120.7−1.3, 2.7
Indiaa1983–20002.2b2000–20046.02004–20120.82003–20121.3−0.3, 3.0
Israel1963–19871.0b1987–199011.81990–19991.51999–2012−0.9b2003–2012−0.91.6, −0.2
Philippinesa1983–20060.82006–2012−2.5b2003–2012−1.4−2.9, 0.1
Thailanda1983–20123.3b2003–20123.32.8, 3.7b
Turkeya1998–20122.6b2003–20122.61.8, 3.4b
Kuwait1998–20122.9b2003–20122.91.8, 4.1b
Europe
Austria1998–20120.02003–20120.0−0.4, 0.3
Belarus1983–19933.8b1993–20121.8b2003–20121.81.5, 2.1b
Bulgaria1998–20032.6b2003–20120.52003–20120.5−0.1, 1.1
Croatia1988–19995.0b1999–20120.82003–20120.80.0, 1.6b
Cyprus1998–20121.8b2003–20121.80.9, 2.8b
Czech Republic1983–20032.4b2003–20120.72003–20120.7−0.4, 1.7
Denmark1953–20021.4b2002–2006−6.22006–200910.32009–2012−7.7b2003–20120.3−4.0, 4.7
Estonia1983–20121.9b2003–20121.91.7, 2.2b
Francea1977–20032.3b2003–2012−0.42003–2012−0.4−1.3, 0.5
Germany1973–20121.7b2003–20121.71.5, 1.8b
Iceland1958–20121.7b2003–20121.71.5, 1.9b
Ireland1994–20121.7b2003–20121.71.3, 2.0b
Italya1978–1984−1.31984–20003.0b2000–2012−0.12003–2012−0.1−0.8, 0.5
Lithuania1988–19974.2b1997–20121.4b2003–20121.40.8, 2.1b
Malta1993–20121.0b2003–20121.00.4, 1.6b
Netherlands1989–19934.5b1993–1997−0.71997–20002.92000–20120.8b2003–20120.80.5, 1.1b
Norway1953–19761.4b1976–19900.7b1990–20013.4b2001–2012−0.32003–2012−0.3−0.9, 0.3
Polanda1998–20015.72001–2004−6.22004–20121.9b2003–20120.9−0.9, 2.8
Slovakia1971–1973−6.71973–20102.1b2001–20102.12.0, 2.2b
Slovenia1983–19876.6b1987–1991−1.41991–19993.6b1999–20120.7b2003–20120.70.1, 1.4b
Spaina1976–19992.3b1999–20120.62003–20120.6−0.2, 1.5
Switzerlanda1973–1987−1.0b1987–20002.3b2000–2012−0.22003–2012−0.2−0.9, 0.5
United Kingdoma1978–19880.9b1988–19915.31991–19991.6b1999–20120.5b2003–20120.50.2, 0.8b
Oceania
Australia1978–19972.6b1997–20120.22003–20120.2−0.3, 0.7
New Zealand1983–19903.7b1990–1993−2.91993–19993.0b1999–20120.02003–20120.0−0.6, 0.5
Trend 1Trend 2Trend 3Trend 4Most Recent Available 10 Years
Region and PopulationPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPC95% CI
Africa
Ugandaa1993–20123.1b2003–20123.11.7, 4.4b
Americas
Canada1983–19911.9b1991–2012−0.12003–2012−0.1−0.3, 0.1
United States (NPCR, Black)1998–20120.3b2003–20120.30.1, 0.5b
United States (NPCR, White)1998–20010.02001–2004−3.32004–2012−0.22003–2012−0.6−1.2, 0.0b
United States (SEER, White)1978–19872.9b1987–20010.5b2001–2004−3.62004–2012−0.12003–2012−0.5−1.2, 0.3
United States (SEER, Black)1978–19883.11988–20120.22003–20120.20.0, 0.4b
Ecuadora1985–20121.8b2003–20121.81.3, 2.4b
Costa Rica1982–1987−3.3b1987–2000−3.6b2000–20111.4b2002–20111.40.3, 2.4b
Colombiaa1983–19961.3b1996–20017.02001–2012−1.6b2003–2012−1.6−3.0, −0.2b
Chilea1998–20120.82003–20120.8−1.0, 2.5
Brazila1993–20043.3b2003–2012−3.1b2003–2012−2.4−4.1, −0.7
Asia
Japana1973–19806.5b1980–19893.5b1989–1992−0.71992–20123.9b2003–20123.93.6, 4.2b
South Korea1993–1995−4.61995–20125.7b2003–20125.75.3, 6.1b
Taiwan1997–20124.8b2003–20124.84.4, 5.2b
Chinaa1988–19980.81998–20017.02001–20121.3b2003–20121.30.3, 2.3b
Hong Kong1983–19930.8b1993–20122.3b2003–20122.32.0, 2.6b
Bahrain1998–20120.72003–20120.7−1.3, 2.7
Indiaa1983–20002.2b2000–20046.02004–20120.82003–20121.3−0.3, 3.0
Israel1963–19871.0b1987–199011.81990–19991.51999–2012−0.9b2003–2012−0.91.6, −0.2
Philippinesa1983–20060.82006–2012−2.5b2003–2012−1.4−2.9, 0.1
Thailanda1983–20123.3b2003–20123.32.8, 3.7b
Turkeya1998–20122.6b2003–20122.61.8, 3.4b
Kuwait1998–20122.9b2003–20122.91.8, 4.1b
Europe
Austria1998–20120.02003–20120.0−0.4, 0.3
Belarus1983–19933.8b1993–20121.8b2003–20121.81.5, 2.1b
Bulgaria1998–20032.6b2003–20120.52003–20120.5−0.1, 1.1
Croatia1988–19995.0b1999–20120.82003–20120.80.0, 1.6b
Cyprus1998–20121.8b2003–20121.80.9, 2.8b
Czech Republic1983–20032.4b2003–20120.72003–20120.7−0.4, 1.7
Denmark1953–20021.4b2002–2006−6.22006–200910.32009–2012−7.7b2003–20120.3−4.0, 4.7
Estonia1983–20121.9b2003–20121.91.7, 2.2b
Francea1977–20032.3b2003–2012−0.42003–2012−0.4−1.3, 0.5
Germany1973–20121.7b2003–20121.71.5, 1.8b
Iceland1958–20121.7b2003–20121.71.5, 1.9b
Ireland1994–20121.7b2003–20121.71.3, 2.0b
Italya1978–1984−1.31984–20003.0b2000–2012−0.12003–2012−0.1−0.8, 0.5
Lithuania1988–19974.2b1997–20121.4b2003–20121.40.8, 2.1b
Malta1993–20121.0b2003–20121.00.4, 1.6b
Netherlands1989–19934.5b1993–1997−0.71997–20002.92000–20120.8b2003–20120.80.5, 1.1b
Norway1953–19761.4b1976–19900.7b1990–20013.4b2001–2012−0.32003–2012−0.3−0.9, 0.3
Polanda1998–20015.72001–2004−6.22004–20121.9b2003–20120.9−0.9, 2.8
Slovakia1971–1973−6.71973–20102.1b2001–20102.12.0, 2.2b
Slovenia1983–19876.6b1987–1991−1.41991–19993.6b1999–20120.7b2003–20120.70.1, 1.4b
Spaina1976–19992.3b1999–20120.62003–20120.6−0.2, 1.5
Switzerlanda1973–1987−1.0b1987–20002.3b2000–2012−0.22003–2012−0.2−0.9, 0.5
United Kingdoma1978–19880.9b1988–19915.31991–19991.6b1999–20120.5b2003–20120.50.2, 0.8b
Oceania
Australia1978–19972.6b1997–20120.22003–20120.2−0.3, 0.7
New Zealand1983–19903.7b1990–1993−2.91993–19993.0b1999–20120.02003–20120.0−0.6, 0.5

Abbreviations: AAPC, average annual percent change; CI, confidence interval; NPCR, National Program of Cancer Registries; SEER, Surveillance, Epidemiology, and End Results Program.

a Denotes regional population-based cancer registry.

bP value<0.05.

Table 1
Open in new tab

Trends in Age-Standardized Incidence Rates of Breast Cancer, Multiple Countries, 1973–2012

Trend 1Trend 2Trend 3Trend 4Most Recent Available 10 Years
Region and PopulationPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPC95% CI
Africa
Ugandaa1993–20123.1b2003–20123.11.7, 4.4b
Americas
Canada1983–19911.9b1991–2012−0.12003–2012−0.1−0.3, 0.1
United States (NPCR, Black)1998–20120.3b2003–20120.30.1, 0.5b
United States (NPCR, White)1998–20010.02001–2004−3.32004–2012−0.22003–2012−0.6−1.2, 0.0b
United States (SEER, White)1978–19872.9b1987–20010.5b2001–2004−3.62004–2012−0.12003–2012−0.5−1.2, 0.3
United States (SEER, Black)1978–19883.11988–20120.22003–20120.20.0, 0.4b
Ecuadora1985–20121.8b2003–20121.81.3, 2.4b
Costa Rica1982–1987−3.3b1987–2000−3.6b2000–20111.4b2002–20111.40.3, 2.4b
Colombiaa1983–19961.3b1996–20017.02001–2012−1.6b2003–2012−1.6−3.0, −0.2b
Chilea1998–20120.82003–20120.8−1.0, 2.5
Brazila1993–20043.3b2003–2012−3.1b2003–2012−2.4−4.1, −0.7
Asia
Japana1973–19806.5b1980–19893.5b1989–1992−0.71992–20123.9b2003–20123.93.6, 4.2b
South Korea1993–1995−4.61995–20125.7b2003–20125.75.3, 6.1b
Taiwan1997–20124.8b2003–20124.84.4, 5.2b
Chinaa1988–19980.81998–20017.02001–20121.3b2003–20121.30.3, 2.3b
Hong Kong1983–19930.8b1993–20122.3b2003–20122.32.0, 2.6b
Bahrain1998–20120.72003–20120.7−1.3, 2.7
Indiaa1983–20002.2b2000–20046.02004–20120.82003–20121.3−0.3, 3.0
Israel1963–19871.0b1987–199011.81990–19991.51999–2012−0.9b2003–2012−0.91.6, −0.2
Philippinesa1983–20060.82006–2012−2.5b2003–2012−1.4−2.9, 0.1
Thailanda1983–20123.3b2003–20123.32.8, 3.7b
Turkeya1998–20122.6b2003–20122.61.8, 3.4b
Kuwait1998–20122.9b2003–20122.91.8, 4.1b
Europe
Austria1998–20120.02003–20120.0−0.4, 0.3
Belarus1983–19933.8b1993–20121.8b2003–20121.81.5, 2.1b
Bulgaria1998–20032.6b2003–20120.52003–20120.5−0.1, 1.1
Croatia1988–19995.0b1999–20120.82003–20120.80.0, 1.6b
Cyprus1998–20121.8b2003–20121.80.9, 2.8b
Czech Republic1983–20032.4b2003–20120.72003–20120.7−0.4, 1.7
Denmark1953–20021.4b2002–2006−6.22006–200910.32009–2012−7.7b2003–20120.3−4.0, 4.7
Estonia1983–20121.9b2003–20121.91.7, 2.2b
Francea1977–20032.3b2003–2012−0.42003–2012−0.4−1.3, 0.5
Germany1973–20121.7b2003–20121.71.5, 1.8b
Iceland1958–20121.7b2003–20121.71.5, 1.9b
Ireland1994–20121.7b2003–20121.71.3, 2.0b
Italya1978–1984−1.31984–20003.0b2000–2012−0.12003–2012−0.1−0.8, 0.5
Lithuania1988–19974.2b1997–20121.4b2003–20121.40.8, 2.1b
Malta1993–20121.0b2003–20121.00.4, 1.6b
Netherlands1989–19934.5b1993–1997−0.71997–20002.92000–20120.8b2003–20120.80.5, 1.1b
Norway1953–19761.4b1976–19900.7b1990–20013.4b2001–2012−0.32003–2012−0.3−0.9, 0.3
Polanda1998–20015.72001–2004−6.22004–20121.9b2003–20120.9−0.9, 2.8
Slovakia1971–1973−6.71973–20102.1b2001–20102.12.0, 2.2b
Slovenia1983–19876.6b1987–1991−1.41991–19993.6b1999–20120.7b2003–20120.70.1, 1.4b
Spaina1976–19992.3b1999–20120.62003–20120.6−0.2, 1.5
Switzerlanda1973–1987−1.0b1987–20002.3b2000–2012−0.22003–2012−0.2−0.9, 0.5
United Kingdoma1978–19880.9b1988–19915.31991–19991.6b1999–20120.5b2003–20120.50.2, 0.8b
Oceania
Australia1978–19972.6b1997–20120.22003–20120.2−0.3, 0.7
New Zealand1983–19903.7b1990–1993−2.91993–19993.0b1999–20120.02003–20120.0−0.6, 0.5
Trend 1Trend 2Trend 3Trend 4Most Recent Available 10 Years
Region and PopulationPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPCPeriodAAPC95% CI
Africa
Ugandaa1993–20123.1b2003–20123.11.7, 4.4b
Americas
Canada1983–19911.9b1991–2012−0.12003–2012−0.1−0.3, 0.1
United States (NPCR, Black)1998–20120.3b2003–20120.30.1, 0.5b
United States (NPCR, White)1998–20010.02001–2004−3.32004–2012−0.22003–2012−0.6−1.2, 0.0b
United States (SEER, White)1978–19872.9b1987–20010.5b2001–2004−3.62004–2012−0.12003–2012−0.5−1.2, 0.3
United States (SEER, Black)1978–19883.11988–20120.22003–20120.20.0, 0.4b
Ecuadora1985–20121.8b2003–20121.81.3, 2.4b
Costa Rica1982–1987−3.3b1987–2000−3.6b2000–20111.4b2002–20111.40.3, 2.4b
Colombiaa1983–19961.3b1996–20017.02001–2012−1.6b2003–2012−1.6−3.0, −0.2b
Chilea1998–20120.82003–20120.8−1.0, 2.5
Brazila1993–20043.3b2003–2012−3.1b2003–2012−2.4−4.1, −0.7
Asia
Japana1973–19806.5b1980–19893.5b1989–1992−0.71992–20123.9b2003–20123.93.6, 4.2b
South Korea1993–1995−4.61995–20125.7b2003–20125.75.3, 6.1b
Taiwan1997–20124.8b2003–20124.84.4, 5.2b
Chinaa1988–19980.81998–20017.02001–20121.3b2003–20121.30.3, 2.3b
Hong Kong1983–19930.8b1993–20122.3b2003–20122.32.0, 2.6b
Bahrain1998–20120.72003–20120.7−1.3, 2.7
Indiaa1983–20002.2b2000–20046.02004–20120.82003–20121.3−0.3, 3.0
Israel1963–19871.0b1987–199011.81990–19991.51999–2012−0.9b2003–2012−0.91.6, −0.2
Philippinesa1983–20060.82006–2012−2.5b2003–2012−1.4−2.9, 0.1
Thailanda1983–20123.3b2003–20123.32.8, 3.7b
Turkeya1998–20122.6b2003–20122.61.8, 3.4b
Kuwait1998–20122.9b2003–20122.91.8, 4.1b
Europe
Austria1998–20120.02003–20120.0−0.4, 0.3
Belarus1983–19933.8b1993–20121.8b2003–20121.81.5, 2.1b
Bulgaria1998–20032.6b2003–20120.52003–20120.5−0.1, 1.1
Croatia1988–19995.0b1999–20120.82003–20120.80.0, 1.6b
Cyprus1998–20121.8b2003–20121.80.9, 2.8b
Czech Republic1983–20032.4b2003–20120.72003–20120.7−0.4, 1.7
Denmark1953–20021.4b2002–2006−6.22006–200910.32009–2012−7.7b2003–20120.3−4.0, 4.7
Estonia1983–20121.9b2003–20121.91.7, 2.2b
Francea1977–20032.3b2003–2012−0.42003–2012−0.4−1.3, 0.5
Germany1973–20121.7b2003–20121.71.5, 1.8b
Iceland1958–20121.7b2003–20121.71.5, 1.9b
Ireland1994–20121.7b2003–20121.71.3, 2.0b
Italya1978–1984−1.31984–20003.0b2000–2012−0.12003–2012−0.1−0.8, 0.5
Lithuania1988–19974.2b1997–20121.4b2003–20121.40.8, 2.1b
Malta1993–20121.0b2003–20121.00.4, 1.6b
Netherlands1989–19934.5b1993–1997−0.71997–20002.92000–20120.8b2003–20120.80.5, 1.1b
Norway1953–19761.4b1976–19900.7b1990–20013.4b2001–2012−0.32003–2012−0.3−0.9, 0.3
Polanda1998–20015.72001–2004−6.22004–20121.9b2003–20120.9−0.9, 2.8
Slovakia1971–1973−6.71973–20102.1b2001–20102.12.0, 2.2b
Slovenia1983–19876.6b1987–1991−1.41991–19993.6b1999–20120.7b2003–20120.70.1, 1.4b
Spaina1976–19992.3b1999–20120.62003–20120.6−0.2, 1.5
Switzerlanda1973–1987−1.0b1987–20002.3b2000–2012−0.22003–2012−0.2−0.9, 0.5
United Kingdoma1978–19880.9b1988–19915.31991–19991.6b1999–20120.5b2003–20120.50.2, 0.8b
Oceania
Australia1978–19972.6b1997–20120.22003–20120.2−0.3, 0.7
New Zealand1983–19903.7b1990–1993−2.91993–19993.0b1999–20120.02003–20120.0−0.6, 0.5

Abbreviations: AAPC, average annual percent change; CI, confidence interval; NPCR, National Program of Cancer Registries; SEER, Surveillance, Epidemiology, and End Results Program.

a Denotes regional population-based cancer registry.

bP value<0.05.

The average annual percent change for the 10 most recent years is also presented in Table 1. No significant change was observed in most Western countries/regions. In contrast, an upward trend was observed for Uganda, NPCR data for Black persons, Ecuador, Costa Rica, Japan, South Korea, Taiwan, China, Hong Kong, Thailand, Turkey, Kuwait, Belarus, Cyprus, Estonia, Iceland, Ireland, Lithuania, Malta, the Netherlands, Slovakia, and the United Kingdom. Colombia, Brazil, and Israel showed a slightly declining trend in the 10 most recent years.

The age-specific breast cancer incidence rates by period and birth cohort are presented in Web Figures 2 and 3. In most Western countries/regions, the age-specific breast cancer incidence rates initially rose rapidly with age. They then slowed at roughly age 50 years (“Clemmensen’s hook”) (17), whether by period or by cohort. In contrast, in most Asian countries/regions, by cohort, the rates rose with age and show Clemmensen’s hook; however, by period, the rates increased with age, peaked at ages 45–54 years, and then declined or stayed flat.

Age-period-cohort analysis

The net drifts are displayed in Table 2. South Korea, Taiwan, Japan, Thailand, and Turkey were the 5 countries with the largest net drifts (and significantly larger than zero). Most of the Western countries/regions had minimal net drifts.

Table 2
Open in new tab

Net Drifts Derived From an Age-Period-Cohort Analysis of Global Breast Cancer Incidence Rates, 1997–2011

Country or RegionNet Drift95% CI
South Korea5.895.54, 6.32a
Taiwan4.844.63, 5.05a
Japan3.973.63, 4.32a
Thailand3.762.97, 4.57a
Turkey2.892.45, 3.33a
Kuwait2.301.11, 3.51a
Ecuador2.261.34, 3.18a
Hong Kong2.101.73, 2.47a
Slovakia2.091.54, 2.64a
India2.031.41, 2.65a
China2.011.49, 2.54a
Czech Republic1.910.84, 2.87a
Cyprus1.851.20, 2.35a
Ireland1.771.30, 2.21a
Belarus1.750.88, 2.62a
Denmark1.741.11, 2.16a
Costa Rica1.631.03, 1.80a
Germany1.41−0.54, 3.26
Chile1.340.85, 1.71a
Lithuania1.280.85, 1.71a
Bulgaria1.240.90, 1.59a
LA (Korean)1.23−0.38, 2.87
Netherlands1.211.00, 1.41a
Estonia1.200.46, 1.96a
Uganda1.18−1.72, 4.17
Malta1.07−0.34, 2.50
Slovenia0.990.50, 1.50a
Croatia0.930.26, 1.61a
LA (Chinese)0.92−0.84, 2.70
France0.900.63, 1.17a
Iceland0.71−0.50, 1.94
Norway0.700.22, 1.19a
Spain0.550.16, 0.94a
United Kingdom0.47−0.17, 1.11
United States (NPCR, Asian/Pacific Islander)0.340.03, 0.65a
United States (NPCR, Black)0.340.20, 0.48a
Italy0.25−0.25, 0.76
Brazil0.21−0.83, 1.26
Australia0.17−0.12, 0.46
LA (Hispanic White)0.13−0.29, 0.55
Switzerland0.10−0.30, 0.50
Colombia0.09−0.53, 0.73
Austria0.07−0.30, 0.44
United States (SEER, Black)0.03−0.33, 0.40
New Zealand0.01−0.66, 0.69
Canada−0.04−0.21, 0.13
Bahrain−0.19−1.73, 1.37
Philippines−0.22−0.66, 0.23
Poland−0.25−1.28, 0.79
LA (Japanese)−0.43−2.51, 1.70
LA (Black)−0.52−1.13, 0.10
United States (NPCR, Native Americans)−0.52−1.14, 0.09
LA (non-Hispanic White)−0.62−1.00, −0.23a
Israel−0.80−1.13, −0.47a
United States (SEER, White)−0.85−1.15, −0.55a
United States (NPCR, White)−0.90−1.16, −0.64a
LA (Filipino)−0.97−2.09, 0.17
Country or RegionNet Drift95% CI
South Korea5.895.54, 6.32a
Taiwan4.844.63, 5.05a
Japan3.973.63, 4.32a
Thailand3.762.97, 4.57a
Turkey2.892.45, 3.33a
Kuwait2.301.11, 3.51a
Ecuador2.261.34, 3.18a
Hong Kong2.101.73, 2.47a
Slovakia2.091.54, 2.64a
India2.031.41, 2.65a
China2.011.49, 2.54a
Czech Republic1.910.84, 2.87a
Cyprus1.851.20, 2.35a
Ireland1.771.30, 2.21a
Belarus1.750.88, 2.62a
Denmark1.741.11, 2.16a
Costa Rica1.631.03, 1.80a
Germany1.41−0.54, 3.26
Chile1.340.85, 1.71a
Lithuania1.280.85, 1.71a
Bulgaria1.240.90, 1.59a
LA (Korean)1.23−0.38, 2.87
Netherlands1.211.00, 1.41a
Estonia1.200.46, 1.96a
Uganda1.18−1.72, 4.17
Malta1.07−0.34, 2.50
Slovenia0.990.50, 1.50a
Croatia0.930.26, 1.61a
LA (Chinese)0.92−0.84, 2.70
France0.900.63, 1.17a
Iceland0.71−0.50, 1.94
Norway0.700.22, 1.19a
Spain0.550.16, 0.94a
United Kingdom0.47−0.17, 1.11
United States (NPCR, Asian/Pacific Islander)0.340.03, 0.65a
United States (NPCR, Black)0.340.20, 0.48a
Italy0.25−0.25, 0.76
Brazil0.21−0.83, 1.26
Australia0.17−0.12, 0.46
LA (Hispanic White)0.13−0.29, 0.55
Switzerland0.10−0.30, 0.50
Colombia0.09−0.53, 0.73
Austria0.07−0.30, 0.44
United States (SEER, Black)0.03−0.33, 0.40
New Zealand0.01−0.66, 0.69
Canada−0.04−0.21, 0.13
Bahrain−0.19−1.73, 1.37
Philippines−0.22−0.66, 0.23
Poland−0.25−1.28, 0.79
LA (Japanese)−0.43−2.51, 1.70
LA (Black)−0.52−1.13, 0.10
United States (NPCR, Native Americans)−0.52−1.14, 0.09
LA (non-Hispanic White)−0.62−1.00, −0.23a
Israel−0.80−1.13, −0.47a
United States (SEER, White)−0.85−1.15, −0.55a
United States (NPCR, White)−0.90−1.16, −0.64a
LA (Filipino)−0.97−2.09, 0.17

Abbreviations: CI, confidence interval; LA, Los Angeles; NPCR, National Program of Cancer Registries; SEER, Surveillance, Epidemiology, and End Results Program.

aP value < 0.05

Table 2
Open in new tab

Net Drifts Derived From an Age-Period-Cohort Analysis of Global Breast Cancer Incidence Rates, 1997–2011

Country or RegionNet Drift95% CI
South Korea5.895.54, 6.32a
Taiwan4.844.63, 5.05a
Japan3.973.63, 4.32a
Thailand3.762.97, 4.57a
Turkey2.892.45, 3.33a
Kuwait2.301.11, 3.51a
Ecuador2.261.34, 3.18a
Hong Kong2.101.73, 2.47a
Slovakia2.091.54, 2.64a
India2.031.41, 2.65a
China2.011.49, 2.54a
Czech Republic1.910.84, 2.87a
Cyprus1.851.20, 2.35a
Ireland1.771.30, 2.21a
Belarus1.750.88, 2.62a
Denmark1.741.11, 2.16a
Costa Rica1.631.03, 1.80a
Germany1.41−0.54, 3.26
Chile1.340.85, 1.71a
Lithuania1.280.85, 1.71a
Bulgaria1.240.90, 1.59a
LA (Korean)1.23−0.38, 2.87
Netherlands1.211.00, 1.41a
Estonia1.200.46, 1.96a
Uganda1.18−1.72, 4.17
Malta1.07−0.34, 2.50
Slovenia0.990.50, 1.50a
Croatia0.930.26, 1.61a
LA (Chinese)0.92−0.84, 2.70
France0.900.63, 1.17a
Iceland0.71−0.50, 1.94
Norway0.700.22, 1.19a
Spain0.550.16, 0.94a
United Kingdom0.47−0.17, 1.11
United States (NPCR, Asian/Pacific Islander)0.340.03, 0.65a
United States (NPCR, Black)0.340.20, 0.48a
Italy0.25−0.25, 0.76
Brazil0.21−0.83, 1.26
Australia0.17−0.12, 0.46
LA (Hispanic White)0.13−0.29, 0.55
Switzerland0.10−0.30, 0.50
Colombia0.09−0.53, 0.73
Austria0.07−0.30, 0.44
United States (SEER, Black)0.03−0.33, 0.40
New Zealand0.01−0.66, 0.69
Canada−0.04−0.21, 0.13
Bahrain−0.19−1.73, 1.37
Philippines−0.22−0.66, 0.23
Poland−0.25−1.28, 0.79
LA (Japanese)−0.43−2.51, 1.70
LA (Black)−0.52−1.13, 0.10
United States (NPCR, Native Americans)−0.52−1.14, 0.09
LA (non-Hispanic White)−0.62−1.00, −0.23a
Israel−0.80−1.13, −0.47a
United States (SEER, White)−0.85−1.15, −0.55a
United States (NPCR, White)−0.90−1.16, −0.64a
LA (Filipino)−0.97−2.09, 0.17
Country or RegionNet Drift95% CI
South Korea5.895.54, 6.32a
Taiwan4.844.63, 5.05a
Japan3.973.63, 4.32a
Thailand3.762.97, 4.57a
Turkey2.892.45, 3.33a
Kuwait2.301.11, 3.51a
Ecuador2.261.34, 3.18a
Hong Kong2.101.73, 2.47a
Slovakia2.091.54, 2.64a
India2.031.41, 2.65a
China2.011.49, 2.54a
Czech Republic1.910.84, 2.87a
Cyprus1.851.20, 2.35a
Ireland1.771.30, 2.21a
Belarus1.750.88, 2.62a
Denmark1.741.11, 2.16a
Costa Rica1.631.03, 1.80a
Germany1.41−0.54, 3.26
Chile1.340.85, 1.71a
Lithuania1.280.85, 1.71a
Bulgaria1.240.90, 1.59a
LA (Korean)1.23−0.38, 2.87
Netherlands1.211.00, 1.41a
Estonia1.200.46, 1.96a
Uganda1.18−1.72, 4.17
Malta1.07−0.34, 2.50
Slovenia0.990.50, 1.50a
Croatia0.930.26, 1.61a
LA (Chinese)0.92−0.84, 2.70
France0.900.63, 1.17a
Iceland0.71−0.50, 1.94
Norway0.700.22, 1.19a
Spain0.550.16, 0.94a
United Kingdom0.47−0.17, 1.11
United States (NPCR, Asian/Pacific Islander)0.340.03, 0.65a
United States (NPCR, Black)0.340.20, 0.48a
Italy0.25−0.25, 0.76
Brazil0.21−0.83, 1.26
Australia0.17−0.12, 0.46
LA (Hispanic White)0.13−0.29, 0.55
Switzerland0.10−0.30, 0.50
Colombia0.09−0.53, 0.73
Austria0.07−0.30, 0.44
United States (SEER, Black)0.03−0.33, 0.40
New Zealand0.01−0.66, 0.69
Canada−0.04−0.21, 0.13
Bahrain−0.19−1.73, 1.37
Philippines−0.22−0.66, 0.23
Poland−0.25−1.28, 0.79
LA (Japanese)−0.43−2.51, 1.70
LA (Black)−0.52−1.13, 0.10
United States (NPCR, Native Americans)−0.52−1.14, 0.09
LA (non-Hispanic White)−0.62−1.00, −0.23a
Israel−0.80−1.13, −0.47a
United States (SEER, White)−0.85−1.15, −0.55a
United States (NPCR, White)−0.90−1.16, −0.64a
LA (Filipino)−0.97−2.09, 0.17

Abbreviations: CI, confidence interval; LA, Los Angeles; NPCR, National Program of Cancer Registries; SEER, Surveillance, Epidemiology, and End Results Program.

aP value < 0.05

Figure 1 shows the estimated cohort rate ratios by selected countries/regions listed in decreasing order of net drift (the estimated cohort rate ratios of all countries/regions are shown in Web Figure 4). The cohort effect for breast cancer was particularly prominent in South Korea, Taiwan, Japan, and Thailand. Breast cancer risk in South Korea rose dramatically with the birth cohort. The risks also grew in Taiwan, Japan, and Thailand but slowed down in the recent cohorts, namely those born after 1965. The risk in Thailand appears to increase dramatically in the 1970 birth cohort, but it exhibits a wide confidence interval. The risks for breast cancer initially rose with the birth cohorts in Hong Kong and India, peaked, and then declined in the recent birth cohorts. By contrast, virtually no birth cohort effect was evident in the Philippines; its cohort rate ratio was roughly constant, unlike the other Asian countries/regions.

continues
Figure 1

continues

Open in new tabDownload slide
continues
Figure 1

continues

Open in new tabDownload slide
Incidence rate ratios of breast cancer by birth cohort, and 95% confidence intervals, for selected countries/regions and races/ethnicities, 1997–2011: A) South Korea; B) Taiwan; C) Japan; D) Thailand; E) Hong Kong; F) India; G) Los Angeles, Korean; H) Los Angeles, Chinese; I) National Program of Cancer Registries (NPCR), Asian/Pacific Islanders; J) NPCR, Black; K) Los Angeles, Hispanic White; L) Surveillance, Epidemiology, and End Results Program (SEER), Black; M) Philippines; N) Los Angeles, Japanese; O) Los Angeles, Black; P) NPCR, Native Americans; Q) Los Angeles, non-Hispanic White; R) SEER, White; S) NPCR, White; T) Los Angeles, Filipino.
Figure 1

Incidence rate ratios of breast cancer by birth cohort, and 95% confidence intervals, for selected countries/regions and races/ethnicities, 1997–2011: A) South Korea; B) Taiwan; C) Japan; D) Thailand; E) Hong Kong; F) India; G) Los Angeles, Korean; H) Los Angeles, Chinese; I) National Program of Cancer Registries (NPCR), Asian/Pacific Islanders; J) NPCR, Black; K) Los Angeles, Hispanic White; L) Surveillance, Epidemiology, and End Results Program (SEER), Black; M) Philippines; N) Los Angeles, Japanese; O) Los Angeles, Black; P) NPCR, Native Americans; Q) Los Angeles, non-Hispanic White; R) SEER, White; S) NPCR, White; T) Los Angeles, Filipino.

Open in new tabDownload slide

In the subgroup analysis for Asian immigrants, an at-most negligible birth cohort effect in breast cancer risk for Asian immigrants in Los Angeles, compared with the birth cohort effect of their Asian origin countries, was identified. The Chinese, South Korean, and Japanese cohort rate ratios in Los Angeles were all nearly constant, whereas that of the Filipinos declined slightly. Moreover, an at-most negligible birth cohort effect in breast cancer risk was identified for all ethnic groups in the United States (SEER, White; SEER, Black; NPCR, White; NPCR, Black; NPCR, Asian/Pacific Islanders; and NPCR, Native Americans) and all ethnic groups in Los Angeles.

The longitudinal and cross-sectional age curves of breast cancer incidence rates, categorized by country/region, are presented in Web Figure 5. The longitudinal age curves for all countries/regions initially rose rapidly with age and then slowed at about age 50 (Clemmensen’s hook) (17). By contrast, the cross-sectional age curves of the 11 countries/regions with the largest net drifts (primarily Asian countries/regions) rose with age, peaked at ages 45–54 years, and then declined or stayed flat. The cross-sectional and longitudinal age curves coincided and exhibited the signature Clemmensen’s hook (17) in the rest of the countries/regions with lower net drifts.

DISCUSSION

This global study demonstrated notable birth cohort effects for breast cancer risk in most Asian countries/regions. By contrast, there was virtually no birth cohort effect in Western countries/regions among White and Black ethnic groups or people of Asian descent. Previous studies have suggested that westernization—a process through which societies adopt or become influenced by Western cultures and change their lifestyles, dietary patterns, and reproductive behaviors accordingly—may be the driver of such birth cohort effects (4, 18, 19). Furthermore, a significant positive association between breast cancer incidence and the Human Development Index has been suggested (20, 21). In this study, the birth cohort effects in most Asian countries/regions, except the Philippines, corresponded with the timing of their westernization. Countries/regions that were late in adopting Western cultures showed more substantial birth cohort effects for breast cancer risk compared with those that underwent westernization earlier.

The 4 countries with the most substantial birth cohort effects are South Korea, Taiwan, Japan, and Thailand. Web Figure 6 shows that these countries’ age-standardized incidence rate of brain and central nervous tumors (serving as an internal control (22, 23)) remained stable. This rules out the possibility that the rapidly increasing trends of breast cancer incidences were due to improved case ascertainment over time. These 4 countries all began undergoing Westernization after World War II. Both Hong Kong Chinese and Taiwanese are southern Han Chinese genetically (24). However, the birth cohort effect for breast cancer risk in Taiwan, which was rather pronounced, was similar to that of Japan (4, 7), whereas the birth cohort effect in Hong Kong, which was not as pronounced, was similar to that of India. The timing of westernization could explain this trend: Hong Kong and India became British colonies (in 1858 and 1841, respectively) and were westernized earlier than Japan and Taiwan (a colony of Japan from 1895 to 1945). The Philippines was the first Asian country to adopt Western cultural aspects (it became a Spanish colony in 1565). The Philippines exhibited an absent to minimal birth cohort effect for breast cancer risk. In addition, our study identified virtually no birth cohort effect for breast cancer risk in Asian immigrants in Los Angeles compared with women residing in the countries from which they had emigrated.

Characteristics associated with a Western lifestyle, such as menarche at an early age, delayed age of menopause, obesity, insufficient physical activity, and increased consumption of fat and animal-sourced products, are risk factors for breast cancer (25, 26). Worldwide survey data show that, in women, menarche age has decreased (27–31), natural menopause age has increased (32–36), and the prevalence of insufficient physical activity (37) and obesity (38) have increased over time. Breast cancer cases appear to be rising worldwide because of the consequences of changing reproductive, hormonal, and dietary risk factors (21). Lin et al. (22) indicated that estrogen receptor (ER)-positive breast cancer was most likely associated with exposure to exogenous and endogenous estrogen sources due to westernized lifestyles. Data from the Taiwan Cancer Registry show that most breast cancers (69.3%) were ER-positive. Hart et al. (39) similarly observed that ER-positive tumors constitute the largest proportion of breast cancers, approximately 65% to 70%. We also performed stratified analysis by age (≤50 vs. >50 years old) in the 4 countries with the most substantial birth cohort effects, showing that the birth-cohort effect is more prominent among older women than among younger women (Web Figure 7).

The cross-sectional age curves of breast cancer differ from country to country; however, this curve is confounded by birth cohort effects (40, 41). After adjusting for birth cohort effects, we found that the longitudinal age curves of breast cancer became remarkably similar in all the countries. Sung et al. (9) also found that the birth cohort–adjusted longitudinal age curves of breast cancer were similar between Asian and Western women. The longitudinal age curves for all countries initially rose rapidly with age and then slowed down at approximately age 50. Clemmensen first described this pattern, later known as Clemmensen’s hook (17).

Most international studies have compared only one Western country/region to only one or a few Asian countries (7, 9, 42–44). These studies have identified significant birth cohort effects in most Asian countries. However, because these studies have used varying methodologies, it is not easy to compare their results directly regarding the birth cohort effect. The present study is, to our knowledge, the first to evaluate the global patterns and trends in breast cancer incidence rates using APC analysis. Our study indicated that countries that were late in adopting Western cultures exhibited more substantial birth cohort effects compared with those that underwent westernization earlier.

Mammography screening may increase breast cancer incidence rates by early detection of breast tumors (45–47). Mammography became widespread during the 1980s, and the coverage rate is estimated to be over 70% in the United States and other developed Western countries (48). However, in most Asian countries, no national population-based breast cancer screening programs have been implemented due to inadequate resources (49). A few Asian countries (e.g., Japan, South Korea, Taiwan) do have nationwide mammography screening programs; however, the programs were initiated later (in the 2000s) (50–52) and have achieved lower screening rates (12% to 61%) (53–55) compared with those of the United States and developed Western countries (48). Taiwan initiated nationwide mammography screening programs in 2004, and the percentage of earlier stages detected increased only slightly (Web Figure 8). The screening programs themselves may not explain the considerable increase in breast cancer incidence among women in Asian countries during our study period, 1997–2011.

One strength of our study was that we used available, updated high-quality population-based data from 47 countries/regions across 5 continents to examine the global patterns of breast cancer incidence rates. Web Table 1 (data extracted from the study of Allemani et al. (56)) shows that of the 47 registries used in this study, the coverage of 25 (53.2%) registries was 100%, and of 31 (66.0%) registries more than 50%.

However, few data were available to perform subgroup analysis according to breast cancer molecular subtype (ER, progesterone receptor, or human epidermal growth factor receptor 2 status) or cancer stage. We urge cancer registries worldwide to collect molecular subtype and stage information. Finally, it should be noted that this was an ecological study, and inference may be subject to the ecological fallacy (57).

In conclusion, this global study demonstrated notable birth cohort effects for breast cancer risk in most Asian countries but virtually no birth cohort effect in Western countries. The timing of westernization was associated with birth cohort effects. Countries that adopted Western cultures later exhibited more substantial birth cohort effects for breast cancer risk than countries that underwent westernization earlier.

ACKNOWLEDGMENTS

Author affiliations: Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan (Yi-Chu Chen, Shih-Yung Su, Jing-Rong Jhuang, Chun-Ju Chiang, Wen-Chung Lee); Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan (Wan-Ching Lien); Department of Emergency Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan (Wan-Ching Lien); and Taiwan Cancer Registry, Taipei, Taiwan (Jing-Rong Jhuang, Chun-Ju Chiang, Ya-Wen Yang, Wen-Chung Lee).

This work was supported by grants from the Health Promotion Administration, the Ministry of Health and Welfare in Taiwan (A1101009; tobacco control and health-care funds), the Ministry of Science and Technology in Taiwan (MOST 108-3017-F-002-001, MOST 108-2314-B-002-127-MY3, and MOST 111-2314-B-002-089-MY3), and the Innovation and Policy Center for Population Health and Sustainable Environment (Population Health Research Center, PHRC) from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan (NTU-109L900308).

This study was approved by the Data Release Review Board of the Health Promotion Administration, Ministry of Health and Welfare in Taiwan, which waived the requirement for informed consent.

The cancer registry data from the International Agency for Research on Cancer can be obtained at https://ci5.iarc.fr/CI5plus/Pages/download.aspx. The cancer registry data from Taiwan in this study are available from the corresponding author on request.

The views expressed in this article are those of the authors only. The content of this research may not represent the opinion of the Health Promotion Administration, Ministry of Health and Welfare in Taiwan.

Conflict of interest: none declared.

REFERENCES

1.

World Health Organization
. Breast cancer now most common form of cancer: WHO taking action.
2021
. https://www.who.int/news/item/03-02-2021-breast-cancer-now-most-common-form-of-cancer-who-taking-action.
Accessed February 4, 2021
.

2.

Heer
E
,
Harper
A
,
Escandor
N
, et al.
Global burden and trends in premenopausal and postmenopausal breast cancer: a population-based study
.
Lancet Glob Health.
2020
;
8
(
8
):
e1027
–
e1037
.

Google Scholar

Crossref
Search ADS
PubMed

 
3.

Anderson
WF
,
Chatterjee
N
,
Ershler
WB
, et al.
Estrogen receptor breast cancer phenotypes in the Surveillance, Epidemiology, and End Results database
.
Breast Cancer Res Treat.
2002
;
76
(
1
):
27
–
36
.

Google Scholar

Crossref
Search ADS
PubMed

 
4.

Shin
HR
,
Joubert
C
,
Boniol
M
, et al.
Recent trends and patterns in breast cancer incidence among Eastern and Southeastern Asian women
.
Cancer Causes Control.
2010
;
21
(
11
):
1777
–
1785
.

Google Scholar

Crossref
Search ADS
PubMed

 
5.

Lin
CH
,
Liau
JY
,
Lu
YS
, et al.
Molecular subtypes of breast cancer emerging in young women in Taiwan: evidence for more than just westernization as a reason for the disease in Asia
.
Cancer Epidemiol Biomarkers Prev.
2009
;
18
(
6
):
1807
–
1814
.

Google Scholar

Crossref
Search ADS
PubMed

 
6.

Leong
SPL
,
Shen
ZZ
,
Liu
TJ
, et al.
Is breast cancer the same disease in Asian and Western countries?
World J Surg.
2010
;
34
(
10
):
2308
–
2324
.

Google Scholar

Crossref
Search ADS
PubMed

 
7.

Shen
YC
,
Chang
CJ
,
Hsu
C
, et al.
Significant difference in the trends of female breast cancer incidence between Taiwanese and Caucasian Americans: implications from age-period-cohort analysis
.
Cancer Epidemiol Biomarkers Prev.
2005
;
14
(
8
):
1986
–
1990
.

Google Scholar

Crossref
Search ADS
PubMed

 
8.

Sung
H
,
Rosenberg
PS
,
Chen
WQ
, et al.
The impact of breast cancer-specific birth cohort effects among younger and older Chinese populations
.
Int J Cancer.
2016
;
139
(
3
):
527
–
534
.

Google Scholar

Crossref
Search ADS
PubMed

 
9.

Sung
H
,
Rosenberg
PS
,
Chen
WQ
, et al.
Female breast cancer incidence among Asian and Western populations: more similar than expected
.
J Natl Cancer Inst.
2015
;
107
(
7
):djv107.

Google Scholar

OpenURL Placeholder Text

 
10.

Leung
GM
,
Thach
TQ
,
Lam
TH
, et al.
Trends in breast cancer incidence in Hong Kong between 1973 and 1999: an age-period-cohort analysis
.
Br J Cancer.
2002
;
87
(
9
):
982
–
988
.

Google Scholar

Crossref
Search ADS
PubMed

 
11.

Bray
F
,
Ferlay
J
,
Laversanne
M
, et al.
Cancer Incidence in Five Continents: inclusion criteria, highlights from volume X and the global status of cancer registration
.
Int J Cancer.
2015
;
137
(
9
):
2060
–
2071
.

Google Scholar

Crossref
Search ADS
PubMed

 
12.

Chiang
CJ
,
You
SL
,
Chen
CJ
, et al.
Quality assessment and improvement of nationwide cancer registration system in Taiwan: a review
.
Jpn J Clin Oncol.
2015
;
45
(
3
):
291
–
296
.

Google Scholar

Crossref
Search ADS
PubMed

 
13.

Chiang
CJ
,
Wang
YW
,
Lee
WC
.
Taiwan’s Nationwide Cancer Registry System of 40 years: past, present, and future
.
J Formos Med Assoc.
2019
;
118
(
5
):
856
–
858
.

Google Scholar

Crossref
Search ADS
PubMed

 
14.

Kim
HJ
,
Fay
MP
,
Feuer
EJ
, et al.
Permutation tests for joinpoint regression with applications to cancer rates
.
Stat Med.
2000
;
19
(
3
):
335
–
351
.

Google Scholar

Crossref
Search ADS
PubMed

 
15.

Rosenberg
PS
,
Check
DP
,
Anderson
WF
.
A web tool for age-period-cohort analysis of cancer incidence and mortality rates
.
Cancer Epidemiol Biomarkers Prev.
2014
;
23
(
11
):
2296
–
2302
.

Google Scholar

Crossref
Search ADS
PubMed

 
16.

National Cancer Institute
. APC web tool.
Published November 10, 2014
. https://analysistools.nci.nih.gov/apc/.
Accessed January 1, 2021
.

17.

Clemmesen
J
.
Carcinoma of the breast; results from statistical research
.
Br J Radiol.
1948
;
21
(
252
):
583
–
590
.

Google Scholar

Crossref
Search ADS
PubMed

 
18.

McTiernan
A
.
Behavioral risk factors in breast cancer: can risk be modified?
Oncologist.
2003
;
8
(
4
):
326
–
334
.

Google Scholar

Crossref
Search ADS
PubMed

 
19.

Gerber
B
,
Müller
H
,
Reimer
T
, et al.
Nutrition and lifestyle factors on the risk of developing breast cancer
.
Breast Cancer Res Treat.
2003
;
79
(
2
):
265
–
276
.

Google Scholar

Crossref
Search ADS
PubMed

 
20.

Ghoncheh
M
,
Mohammadian-Hafshejani
A
,
Salehiniya
H
.
Incidence and mortality of breast cancer and their relationship to development in Asia
.
Asian Pac J Cancer Prev.
2015
;
16
(
14
):
6081
–
6087
.

Google Scholar

Crossref
Search ADS
PubMed

 
21.

Bray
F
,
Jemal
A
,
Grey
N
, et al.
Global cancer transitions according to the Human Development Index (2008–2030): a population-based study
.
Lancet Oncol.
2012
;
13
(
8
):
790
–
801
.

Google Scholar

Crossref
Search ADS
PubMed

 
22.

Lin
CH
,
Chen
YC
,
Chiang
CJ
, et al.
The emerging epidemic of estrogen-related cancers in young women in a developing Asian country
.
Int J Cancer.
2012
;
130
(
11
):
2629
–
2637
.

Google Scholar

Crossref
Search ADS
PubMed

 
23.

Chang
MH
,
Chen
CJ
,
Lai
MS
, et al.
Universal hepatitis B vaccination in Taiwan and the incidence of hepatocellular carcinoma in children. Taiwan Childhood Hepatoma Study Group
.
N Engl J Med.
1997
;
336
(
26
):
1855
–
1859
.

Google Scholar

Crossref
Search ADS
PubMed

 
24.

Chen
CH
,
Yang
JH
,
Chiang
CWK
, et al.
Population structure of Han Chinese in the modern Taiwanese population based on 10,000 participants in the Taiwan Biobank project
.
Hum Mol Genet.
2016
;
25
(
24
):
5321
–
5331
.

Google Scholar

PubMed
OpenURL Placeholder Text

 
25.

Bray
F
,
McCarron
P
,
Parkin
DM
.
The changing global patterns of female breast cancer incidence and mortality
.
Breast Cancer Res.
2004
;
6
(
6
):
229
–
239
.

Google Scholar

Crossref
Search ADS
PubMed

 
26.

Rojas
K
,
Stuckey
A
.
Breast cancer epidemiology and risk factors
.
Clin Obstet Gynecol.
2016
;
59
(
4
):
651
–
672
.

Google Scholar

Crossref
Search ADS
PubMed

 
27.

Demerath
EW
,
Towne
B
,
Chumlea
WC
, et al.
Recent decline in age at menarche: the Fels Longitudinal Study
.
Am J Hum Biol.
2004
;
16
(
4
):
453
–
457
.

Google Scholar

Crossref
Search ADS
PubMed

 
28.

Huen
KF
,
Leung
SS
,
Lau
JT
, et al.
Secular trend in the sexual maturation of southern Chinese girls
.
Acta Paediatr.
1997
;
86
(
10
):
1121
–
1124
.

Google Scholar

Crossref
Search ADS
PubMed

 
29.

Park
SH
,
Shim
YK
,
Kim
HS
, et al.
Age and seasonal distribution of menarche in Korean girls
.
J Adolesc Health.
1999
;
25
(
2
):
97
.

Google Scholar

PubMed
OpenURL Placeholder Text

 
30.

Hwang
JY
,
Shin
C
,
Frongillo
EA
, et al.
Secular trend in age at menarche for South Korean women born between 1920 and 1986: the Ansan Study
.
Ann Hum Biol.
2003
;
30
(
4
):
434
–
442
.

Google Scholar

Crossref
Search ADS
PubMed

 
31.

Chang
S-R
,
Chen
K-H
.
Age at menarche of three-generation families in Taiwan
.
Ann Hum Biol.
2008
;
35
(
4
):
394
–
405
.

Google Scholar

Crossref
Search ADS
PubMed

 
32.

Shen
T-Y
,
Chen
H-J
,
Pan
W-H
, et al.
Secular trends and associated factors of age at natural menopause in Taiwanese women
.
Menopause.
2019
;
26
(
5
):
499
–
505
.

Google Scholar

Crossref
Search ADS
PubMed

 
33.

Park
CY
,
Lim
JY
,
Park
HY
.
Age at natural menopause in Koreans: secular trends and influences thereon
.
Menopause.
2018
;
25
(
4
):
423
–
429
.

Google Scholar

Crossref
Search ADS
PubMed

 
34.

Costanian
C
,
McCague
H
,
Tamim
H
.
Age at natural menopause and its associated factors in Canada: cross-sectional analyses from the Canadian Longitudinal Study on Aging
.
Menopause.
2018
;
25
(
3
):
265
–
272
.

Google Scholar

Crossref
Search ADS
PubMed

 
35.

Dratva
J
,
Gómez Real
F
,
Schindler
C
, et al.
Is age at menopause increasing across Europe? Results on age at menopause and determinants from two population-based studies
.
Menopause.
2009
;
16
(
2
):
385
–
394
.

Google Scholar

Crossref
Search ADS
PubMed

 
36.

Rödström
K
,
Bengtsson
C
,
Milsom
I
, et al.
Evidence for a secular trend in menopausal age: a population study of women in Gothenburg
.
Menopause.
2003
;
10
(
6
):
538
–
543
.

Google Scholar

Crossref
Search ADS
PubMed

 
37.

Guthold
R
,
Stevens
GA
,
Riley
LM
, et al.
Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1.9 million participants
.
Lancet Glob Health.
2018
;
6
(
10
):
e1077
–
e1086
.

Google Scholar

Crossref
Search ADS
PubMed

 
38.

Ng
M
,
Fleming
T
,
Robinson
M
, et al.
Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013
.
Lancet.
2014
;
384
(
9945
):
766
–
781
.

Google Scholar

Crossref
Search ADS
PubMed

 
39.

Hart
CD
,
Migliaccio
I
,
Malorni
L
, et al.
Challenges in the management of advanced, ER-positive, HER2-negative breast cancer
.
Nat Rev Clin Oncol.
2015
;
12
(
9
):
541
–
552
.

Google Scholar

Crossref
Search ADS
PubMed

 
40.

Moolgavkar
SH
,
Stevens
RG
,
Lee
JA
.
Effect of age on incidence of breast cancer in females
.
J Natl Cancer Inst.
1979
;
62
(
3
):
493
–
501
.

Google Scholar

Crossref
Search ADS
PubMed

 
41.

Parkin
DM
,
Bray
FI
,
Devesa
SS
.
Cancer burden in the year 2000. The global picture
.
Eur J Cancer.
2001
;
37
(
suppl 8
):
S4
–
S66
.

Google Scholar

PubMed
OpenURL Placeholder Text

 
42.

Chien
LH
,
Tseng
TJ
,
Chen
CH
, et al.
Comparison of annual percentage change in breast cancer incidence rate between Taiwan and the United States—a smoothed Lexis diagram approach
.
Cancer Med.
2017
;
6
(
7
):
1762
–
1775
.

Google Scholar

Crossref
Search ADS
PubMed

 
43.

Chia
KS
,
Reilly
M
,
Tan
CS
, et al.
Profound changes in breast cancer incidence may reflect changes into a westernized lifestyle: a comparative population-based study in Singapore and Sweden
.
Int J Cancer.
2005
;
113
(
2
):
302
–
306
.

Google Scholar

Crossref
Search ADS
PubMed

 
44.

Matsuno
RK
,
Anderson
WF
,
Yamamoto
S
, et al.
Early- and late-onset breast cancer types among women in the United States and Japan
.
Cancer Epidemiol Biomarkers Prev.
2007
;
16
(
7
):
1437
–
1442
.

Google Scholar

Crossref
Search ADS
PubMed

 
45.

Persson
I
,
Bergström
R
,
Sparén
P
, et al.
Trends in breast cancer incidence in Sweden 1958–1988 by time period and birth cohort
.
Br J Cancer.
1993
;
68
(
6
):
1247
–
1253
.

Google Scholar

Crossref
Search ADS
PubMed

 
46.

Wun
LM
,
Feuer
EJ
,
Miller
BA
.
Are increases in mammographic screening still a valid explanation for trends in breast cancer incidence in the United States?
Cancer Causes Control.
1995
;
6
(
2
):
135
–
144
.

Google Scholar

Crossref
Search ADS
PubMed

 
47.

Rostgaard
K
,
Vaeth
M
,
Holst
H
, et al.
Age-period-cohort modelling of breast cancer incidence in the Nordic countries
.
Stat Med.
2001
;
20
(
1
):
47
–
61
.

Google Scholar

Crossref
Search ADS
PubMed

 
48.

Li
J
,
Shao
Z
.
Mammography screening in less developed countries
.
Springerplus.
2015
;
4
(
1
):
615
.

Google Scholar

Crossref
Search ADS
PubMed

 
49.

Sankaranarayanan
R
,
Ramadas
K
,
Qiao
YL
.
Managing the changing burden of cancer in Asia
.
BMC Med.
2014
;
12
(
1
):
3
.

Google Scholar

Crossref
Search ADS
PubMed

 
50.

Morimoto
T
,
Okazaki
M
,
Endo
T
.
Current status and goals of mammographic screening for breast cancer in Japan
.
Breast Cancer.
2004
;
11
(
1
):
73
–
81
.

Google Scholar

Crossref
Search ADS
PubMed

 
51.

Yoo
KY
.
Cancer control activities in the Republic of Korea
.
Jpn J Clin Oncol.
2008
;
38
(
5
):
327
–
333
.

Google Scholar

Crossref
Search ADS
PubMed

 
52.

Lai
MS
,
Yen
MF
,
Kuo
HS
, et al.
Efficacy of breast-cancer screening for female relatives of breast-cancer-index cases: Taiwan Multicentre Cancer Screening (TAMCAS)
.
Int J Cancer.
1998
;
78
(
1
):
21
–
26
.

Google Scholar

Crossref
Search ADS
PubMed

 
53.

Wu
TY
,
Chen
SL
.
Breast cancer screening practices and related health beliefs among Taiwanese nurses
.
Asia Pac J Oncol Nurs.
2017
;
4
(
2
):
104
–
111
.

Google Scholar

Crossref
Search ADS
PubMed

 
54.

Organisation for Economic Co-operation and Development
. OECD reviews of public health: Japan.
2019
. https://www.oecd.org/japan/oecd-reviews-of-public-health-japan-9789264311602-en.htm.
Accesssed July 11, 2022
.

55.

Choi
E
,
Lee
YY
,
Suh
M
, et al.
Socioeconomic inequalities in cervical and breast cancer screening among women in Korea, 2005–2015
.
Yonsei Med J.
2018
;
59
(
9
):
1026
–
1033
.

Google Scholar

Crossref
Search ADS
PubMed

 
56.

Allemani
C
,
Matsuda
T
,
Di Carlo
V
, et al.
Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries
.
Lancet.
2018
;
391
(
10125
):
1023
–
1075
.

Google Scholar

Crossref
Search ADS
PubMed

 
57.

Chen
YC
,
Ko
PCI
,
Lee
WC
, et al.
Ecological fallacy in COVID-19 epidemiological inference: influenza vaccination rate as an example
.
J Formos Med Assoc.
2021
;
120
(
8
):
1655
–
1656
.

Google Scholar

Crossref
Search ADS
PubMed

 
© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: [email protected].
This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://dbpia.nl.go.kr/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
Topic:
Issue Section:
ORIGINAL CONTRIBUTION
Download all slides
  • Supplementary data

    • Supplementary data

    Web_Material_kwac116 - pdf file