APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots
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The analysis of age-period-cohort (APC) patterns of vital rate changes over time is of great importance for understanding demographic phenomena. Given the limitations of statistical modeling, the use of graphical analyses is often regarded as a more transp
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Lexis surfaces provide an intuitive approach to identify cohort patterns without relying on assumptions of age-period-cohort statistical models.
“Lexis surfaces provide an intuitive approach to identify cohort patterns without relying on assumptions of age–period–cohort statistical models (55).”
From Insights into US life expectancy stagnation from birth cohort mortality dynamics (2026) · cites this paper as [55]
Cites
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Clayton, D., & Schifflers, E. (1987) · Statistics in Medicine · doi:10.1002/sim.4780060405 · Cited by 882 · cited 6× · see citing works
“This term should not be confused with ‘local curvature,’ also referred to as ‘contrast’ and ‘second-order difference’ (Acosta et al. 2019b; Clayton and Schifflers 1987; Holford 1991; Pullum 1980; Tango and Kurashina 1987; Tarone and Chu 1996), which are used to measure the change in the slope of…”
MethodInfluentialInflammatory Exposure and Historical Changes in Human Life-Spans
Finch, C., & Crimmins, E. (2004) · Science · doi:10.1126/science.1092556 · Cited by 763 · cited 2× · see citing works
“Consistent with this idea, the hand-drawn contours indicating cohort mortality improvement patterns presented in the work of Kermack, McKendrick, and McKinlay (1934) have been recognized as a pioneering example of research demonstrating that long-term mortality change tends to follow the birth cohort dimension (Finch…”
BackgroundMethodInfluentialThe estimation of age, period and cohort effects for vital rates.
Holford, T. R. (1983) · Biometrics · doi:10.2307/2531004 · Cited by 647 · cited 6× · see citing works
“While there are infinitely many ways to partition the linear effects into APC components, the curvature components have the same shape and magnitude regardless of the parameterization used to fit the model (Clayton and Schifflers 1987; Holford 1983, 1991).”
BackgroundMethodInfluentialJdanov, D., Jasilionis, D., Shkolnikov, V., & Barbieri, M. (2019) · Encyclopedia of Gerontology and Population Aging · doi:10.1007/978-3-319-69892-2_1102-1 · Cited by 575 · cited 1× · see citing works
“Here, we used mortality data for certain countries drawn from the Human Mortality Database (HMD 2019) to compare not only the curvature ridges of the hump, but the additional features of their changes in magnitude and spread over time and across different countries.”
MethodUnderstanding the effects of age, period, and cohort on incidence and mortality rates.
Holford, T. (1991) · Annual Review of Public Health · doi:10.1146/annurev.pu.12.050191.002233 · Cited by 531 · cited 7× · see citing works
“While there are infinitely many ways to partition the linear effects into APC components, the curvature components have the same shape and magnitude regardless of the parameterization used to fit the model (Clayton and Schifflers 1987; Holford 1983, 1991).”
MethodInfluentialAge–period–cohort models for the Lexis diagram
Carstensen, B. (2007) · Statistics in Medicine · doi:10.1002/sim.2764 · Cited by 506 · cited 2× · see citing works
“Several arithmetic and statistical models have been proposed to identify deviation from trends, such as the Median Polish technique (Keyes and Li 2010; Selvin 2001; Tukey 1977) and the Detrended Age-Period-Cohort models (dAPC) (Carstensen 2007; Clayton and Schifflers 1987; Holford 1983).”
MethodHolford, T. (2005) · Encyclopedia of Biostatistics · doi:10.1002/0470011815.b2a03003 · Cited by 405 · cited 1× · see citing works
“Such curvature would 3 Note that the term ‘curvature’ used here refers to deviations from linear effects, as originally proposed by Holford and used in the APC literature (Clayton and Schifflers 1987; Holford 1983, 1991, 2005; Tango and Kurashina 1987).”
MethodSex mortality differences in The United States: The role of cohort smoking patterns
Preston, S. H., & Wang, H. (2006) · Demography · doi:10.1353/dem.2006.0037 · Cited by 321 · cited 3× · see citing works
“Given this limitation, the use of graphical analyses is often regarded as a more transparent approach to identify APC effects than the use of statistical modeling (Murphy 2010; Preston and Wang 2006; Willets 2004).”
BackgroundMethodInfluentialKeyes, K. M., Utz, R. L., Robinson, W., & Li, G. (2010) · Social Science & Medicine · doi:10.1016/j.socscimed.2009.12.018 · Cited by 292 · cited 2× · see citing works
“The question of whether it is possible to independently isolate these age, period, and cohort (APC) effects on temporal changes in population phenomena has been vigorously debated since the first half of the 20th century (Keyes et al. 2010; Murphy 2010).”
BackgroundLuo, L. (2013) · Demography · doi:10.1007/s13524-013-0243-z · Cited by 285 · cited 1× · see citing works
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
MethodESTIMABLE FUNCTIONS OF AGE, PERIOD, AND COHORT EFFECTS*
Rodgers, W. (1982) · American Sociological Review · doi:10.2307/2095213 · Cited by 280 · cited 2× · see citing works
“…that focus instead on identifying divergence from secular trends (also known as curvature3) in each of the three temporal dimensions (Holford 1983; Rodgers 1982; Tango and Kurashina 1987) are more effective and less polemical than those focused on identifying the dominant patterns of change.”
BackgroundAge, period, and cohort effects in demography: a review.
Hobcraft, J., Menken, J., & Preston, S. (1982) · Population Index · doi:10.1007/978-1-4613-8536-3_4 · Cited by 280 · cited 1× · see citing works
“…presented in the work of Kermack, McKendrick, and McKinlay (1934) have been recognized as a pioneering example of research demonstrating that long-term mortality change tends to follow the birth cohort dimension (Finch and Crimmins 2004; Hobcraft, Menken, and Preston 1982; Preston and Wang 2006).”
BackgroundInfluentialAnalyzing Age-Period-Cohort Data: A Review and Critique
Fosse, E., & Winship, C. (2019) · The Annual review of sociology · doi:10.1146/annurev-soc-073018-022616 · Cited by 220 · cited 2× · see citing works
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
BackgroundMethodThe Cohort Effect: Insights and Explanations
Willets, R. (2004) · British Actuarial Journal · doi:10.1017/s1357321700002762 · Cited by 206 · cited 2× · see citing works
“Given this limitation, the use of graphical analyses is often regarded as a more transparent approach to identify APC effects than the use of statistical modeling (Murphy 2010; Preston and Wang 2006; Willets 2004).”
MethodMortalitySmooth: An R Package for Smoothing Poisson Counts with P-Splines
Camarda, C. (2012) · Journal of Statistical Software · doi:10.18637/jss.v050.i01 · Cited by 180 · cited 6× · see citing works
“2018), MortalitySmooth (Camarda 2012), and HMDHFDplus (Riffe 2015).”
MethodInfluentialThe impossibility of separating age, period and cohort effects.
Bell, A., & Jones, K. (2013) · Social Science & Medicine (1967) · doi:10.1016/j.socscimed.2013.04.029 · Cited by 177 · cited 1× · see citing works
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
MethodContinued Reductions in Mortality at Advanced Ages
Rau, R., Soroko, E., Jasilionis, D., & Vaupel, J. (2008) · Population and Development Review · doi:10.1111/j.1728-4457.2008.00249.x · Cited by 166 · cited 1× · see citing works
“Indicative Lexis diagrams (Willets 2004) and colored Lexis surfaces (Rau et al. 2008, 2018; Richards, Kirkby, and Currie 2006) of these derivatives have been proposed as visualization techniques that could be applied to identify the presence of such patterns in Lexis plots.”
MethodEvaluation of birth cohort patterns in population disease rates.
Tarone, R., & Chu, K. (1996) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a008661 · Cited by 115 · cited 6× · see citing works
“’ This term should not be confused with ‘local curvature,’ also referred to as ‘contrast’ and ‘second-order difference’ (Acosta et al. 2019b; Clayton and Schifflers 1987; Holford 1991; Pullum 1980; Tango and Kurashina 1987; Tarone and Chu 1996), which are used to measure the change in the slope of the effects.”
MethodInfluentialBounding Analyses of Age-Period-Cohort Effects
Fosse, E., & Winship, C. (2019) · Demography · doi:10.1007/s13524-019-00801-6 · Cited by 96 · cited 2× · see citing works
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
BackgroundMethodShould Age-Period-Cohort Studies Return to the Methodologies of the 1970s?
Reither, E., Masters, R. K., Yang, Y., Powers, D., Zheng, H.-L., & Land, K. (2015) · Social Science & Medicine (1967) · doi:10.1016/j.socscimed.2015.01.011 · Cited by 95 · cited 1×
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
MethodDeath-rates in Great Britain and Sweden. Some general regularities and their significance
Kermack, W., McKendrick, A., & McKinlay, P. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.4.678 · Cited by 95 · cited 1× · see citing works
“Consistent with this idea, the hand-drawn contours indicating cohort mortality improvement patterns presented in the work of Kermack, McKendrick, and McKinlay (1934) have been recognized as a pioneering example of research demonstrating that long-term mortality change tends to follow the birth…”
MethodThe Importance of Year of Birth in Two-Dimensional Mortality Data
Richards, S., Kirkby, J., & Currie, I. (2006) · British Actuarial Journal · doi:10.1017/s1357321700004682 · Cited by 89 · cited 1× · see citing works
“Indicative Lexis diagrams (Willets 2004) and colored Lexis surfaces (Rau et al. 2008, 2018; Richards, Kirkby, and Currie 2006) of these derivatives have been proposed as visualization techniques that could be applied to identify the presence of such patterns in Lexis plots.”
MethodGoldstein, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0014826 · Cited by 68 · cited 1× · see citing works
“Goldstein (2011) presented a plot of the hump peaks over time for several countries, and Remund and colleagues (2018) decomposed and plotted the contributions by cause of death in order to analyze several features of the hump in the United States.”
BackgroundSeparating age, period, and cohort effects in white U.S. fertility, 1920–1970
Pullum, T. (1980) · doi:10.1016/0049-089x(80)90013-7 · Cited by 68 · cited 9×
“While there are infinitely many ways to partition the linear effects into APC components, the curvature components have the same shape and magnitude regardless of the parameterization used to fit the model (Clayton and Schifflers 1987; Holford 1983, 1991).”
MethodInfluentialA multi-phase method for estimating cohort effects in age-period contingency table data
Keyes, K., & Li, G.-H. (2010) · Annals of Epidemiology · doi:10.1016/j.annepidem.2010.03.006 · Cited by 57 · cited 1×
“Several arithmetic and statistical models have been proposed to identify deviation from trends, such as the Median Polish technique (Keyes and Li 2010; Selvin 2001; Tukey 1977) and the Detrended Age-Period-Cohort models (dAPC) (Carstensen 2007; Clayton and Schifflers 1987; Holford 1983).”
MethodTango, T., & Kurashina, S. (1987) · Statistics in Medicine · doi:10.1002/sim.4780060608 · Cited by 54 · cited 8×
“’ This term should not be confused with ‘local curvature,’ also referred to as ‘contrast’ and ‘second-order difference’ (Acosta et al. 2019b; Clayton and Schifflers 1987; Holford 1991; Pullum 1980; Tango and Kurashina 1987; Tarone and Chu 1996), which are used to measure the change in the slope of the effects.”
BackgroundMethodInfluentialA Cause-of-Death Decomposition of Young Adult Excess Mortality
Remund, A., Camarda, C., & Riffe, T. (2018) · Demography · doi:10.1007/s13524-018-0680-9 · Cited by 51 · cited 1× · see citing works
“These approaches include applying interpolation techniques (Camarda 2012), extracting the irregularity using decomposition techniques (Remund, Camarda, and Riffe 2018), using detrended APC models (Chauvel, Leist, and Smith 2017), or simply detrending the smoothed vital rates over the selected…”
MethodReexamining the Dominance of Birth Cohort Effects on Mortality.
Murphy, M. (2010) · Population and Development Review · doi:10.1111/j.1728-4457.2010.00334.x · Cited by 48 · cited 4× · see citing works
“Given this limitation, the use of graphical analyses is often regarded as a more transparent approach to identify APC effects than the use of statistical modeling (Murphy 2010; Preston and Wang 2006; Willets 2004).”
BackgroundMethodInfluentialEpidemiologic Analysis: A Case-Oriented Approach
Gange, S., & Cole, S. R. (2002) · doi:10.1093/aje/155.5.485-a · Cited by 35 · cited 1×
“Several arithmetic and statistical models have been proposed to identify deviation from trends, such as the Median Polish technique (Keyes and Li 2010; Selvin 2001; Tukey 1977) and the Detrended Age-Period-Cohort models (dAPC) (Carstensen 2007; Clayton and Schifflers 1987; Holford 1983).”
MethodIncreasing U.S. Mortality Due to Accidental Poisoning: The Role of the Baby Boom Cohort
Miech, R., Koester, S., & Dorsey-Holliman, B. (2011) · Addiction · doi:10.1111/j.1360-0443.2010.03332.x · Cited by 34 · cited 1× · see citing works
“Demographic Research: Volume 41, Article 42 http://www.demographic-research.org 1219 their life course (Acosta et al. 2019a; Miech, Koester, and Dorsey-Holliman 2011; Zang et al. 2019).”
BackgroundVisualizing Mortality Dynamics in the Lexis Diagram
Rau, R., Bohk-Ewald, C., Muszyńska, M., & Vaupel, J. (2017) · BiblioBoard Library Catalog (Open Research Library) · doi:10.1007/978-3-319-64820-0 · Cited by 29 · cited 3× · see citing works
“Indicative Lexis diagrams (Willets 2004) and colored Lexis surfaces (Rau et al. 2008, 2018; Richards, Kirkby, and Currie 2006) of these derivatives have been proposed as visualization techniques that could be applied to identify the presence of such patterns in Lexis plots.”
BackgroundMethodZang, E. X., Zheng, H., Yang, Y. C., & Land, K. C. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyy255 · Cited by 29 · cited 1× · see citing works
“Demographic Research: Volume 41, Article 42 http://www.demographic-research.org 1219 their life course (Acosta et al. 2019a; Miech, Koester, and Dorsey-Holliman 2011; Zang et al. 2019).”
BackgroundKeenan, K. L., Saburova, L., Bobrova, N., Elbourne, D. R., Ashwin, S., & Leon, D. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142993 · Cited by 28 · cited 1× · see citing works
“In the case of Russia, the cohort pattern could be indicative of a longterm mortality disadvantage for those cohorts who entered adulthood in the early 1990s, when the country was undergoing a profound sociohistorical transformation, as well as a severe alcohol abuse epidemic (Keenan et al. 2015).”
BackgroundFitting Age-Period-Cohort Models Using the Intrinsic Estimator: Assumptions and Misapplications
Masters, R. K., Powers, D., Hummer, R., Beck, A. N., Lin, S.-F., & Finch, B. (2016) · Demography · doi:10.1007/s13524-016-0481-y · Cited by 28 · cited 1×
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
MethodAge–period–cohort analysis in the 1870s: Diagrams, stereograms, and the basic differential equation
Keiding, N. (2011) · doi:10.1002/cjs.10121 · Cited by 26 · cited 1×
“It has long been recognized that populations change along the three dimensions of age, period (typically calendar year), and cohort (typically year of birth) (Caselli and Vallin 2005; Keiding 2011).”
BackgroundAcosta, E., Hallman, S. A., Dillon, L. Y., Ouellette, N., Bourbeau, R., Herring, D., Inwood, K., Earn, D., Madrenas, J., Miller, M. S., et al. (2019) · Demography · doi:10.1007/s13524-019-00809-y · Cited by 22 · cited 3× · see citing works
“Demographic Research: Volume 41, Article 42 http://www.demographic-research.org 1219 their life course (Acosta et al. 2019a; Miech, Koester, and Dorsey-Holliman 2011; Zang et al. 2019).”
BackgroundMethodSelf-citationChauvel, L. (2013) · Revue Française de Sociologie · doi:10.3917/rfs.544.0665 · Cited by 22 · cited 2× · see citing works
“Although identifiable, the curvature estimates are average effects that are fixed over the whole length of time (Chauvel 2013).”
BackgroundReading Human Fertility Database and Human Mortality Database data into R
Riffe, T. (2015) · doi:10.4054/mpidr-tr-2015-004 · Cited by 20 · cited 3×
“Cohort age-specific fertility rates (ASFR) were obtained from the Human Fertility Database (HFD 2019) and extracted using the R package HMDHFDplus (Riffe 2015).”
MethodMoore–Penrose Estimators of Age–Period–Cohort Effects: Their Interrelationship and Properties
Fosse, E., & Winship, C. (2018) · Sociological Science · doi:10.15195/v5.a14 · Cited by 19 · cited 1× · see citing works
“Recently, discussions of this topic became even more heated in reaction to the set of methods proposed by Yang and colleagues (Bell and Jones 2013; Fosse and Winship 2018, 2019a; Luo 2013; Masters et al. 2016; Reither et al. 2015; Yang and Land 2013).”
MethodAnalyzing the young adult mortality hump in R with MortHump
Remund, A., Camarda, C., & Riffe, T. (2018) · doi:10.4054/mpidr-tr-2018-003 · Cited by 7
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Grigoriev, P., Klüsener, S., & van Raalte, A. A. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-064249 · Cited by 21 · see citing works
Bramajo, O. N. (2022) · European Journal of Population / Revue européenne de Démographie · doi:10.1007/s10680-022-09610-x · Cited by 25 · see citing works
The boomer penalty: excess mortality among baby boomers in Canada and the United States
Acosta, E., Gagnon, A., Ouellette, N., Bourbeau, R. R., Nepomuceno, M., & van Raalte, A. A. (2020) · doi:10.4054/mpidr-wp-2020-003 · Cited by 5 · see citing works
Self-citationJones, P. M., Minton, J., & Bell, A. (2022) · Quality & Quantity: International Journal of Methodology · doi:10.1007/s11135-022-01498-3 · Cited by 4 · see citing works
“There is also scope to combine the effects found in different countries on to single Lexis ‘curvature’ plots, allowing for interesting cross-national comparison (Acosta and van Raalte 2019).”
BackgroundInsights into US life expectancy stagnation from birth cohort mortality dynamics
Abrams, L., Bramajo, O., van Raalte, A., Myrskylä, M., & Mehta, N. K. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2519356123 · Cited by 6 · see citing works
Self-citationBramajo, O. N. (2023) · Journal of Population Research · doi:10.1007/s12546-023-09323-w · Cited by 3 · see citing works
“…produced a Lexis Surface of the smoothed age-specific death rates (using the smooth functions that the Epi package provides in the apc.fit function), to visually inspect the presence of period or cohort features based on the curvature of the surfaces (Acosta & van Raalte, 2019; Rau et al., 2018).”
Incidence of dementia diagnosis in Denmark, 1986-2023: an age-period-cohort analysis.
Callaway, J., Strozza, C., & Jóhannsson, Ó. (2026) · Social Science & Medicine (1967) · doi:10.1016/j.socscimed.2026.118951 · Cited by 2 · see citing works
Riffe, T., & Aburto, J. (2019) · Demographic Research · doi:10.4054/mpidr-wp-2019-001 · Cited by 1
- Authors
- Acosta, E., & van Raalte, A.
- Affiliations
- Max Planck Institute for Demographic Research (DE)
- Corresponding author
- Acosta, Enrique
- ORCID
- Acosta, Enrique
- Venue
- Demographic Research
- Published
- 2019-11-07
- Volume
- 41
- Pages
- 1205-1234
- ISSN
- 1435-9871 (ISSN-L)
- OpenAlex
- W2983192789
- Cited by
- 12
- References
- 49
- Citations by year
- 2026: 2 · 2024: 1 · 2023: 3 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 1
- FWCI
- 3.40
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Demographic Research (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- H2020 European Research Council (716323)
- Topics
- Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Keywords
- age-period-cohort analysis, mortality trends
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