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Competition in size-structure d populations: mechanisms inducing cohort formation and population cycles: Theoretical Population Biology, Vol. 63, No. 1. (February 2003), pp. 1-16.AM de Roos, L Persson

Source: Theoretical Population Biology, Vol. 63, No. 1. (February 2003), pp. 1-16.
Prolactin levels, breast-feeding and milk production in a cohort of young healthy women from high-risk breast cancer families: implications for breast cancer risk: Familial Cancer, Vol. 7, No. 3. (2008), pp. 221-228.Abstra ct High prolactin levels have been associated with increased breast cancer risk. Prolactin is essential for breast-feeding . Prolactin is lowered primarily by the first full-term pregnancy and not by subsequent pregnancies. The protection from breast cancer conferred by a long breast-feeding duration (>1 year) seems to be much greater for women with BRCA1 mutations (45%) than for women in the general population (4%). One study reported poor milk production to be more common in BRCA1 carriers (75%) than in non-carriers (36%). We aimed to explore the relationships between prolactin levels, breast-feeding duration, milk production and BRCA carrier status in young healthy women from high-risk breast cancer families. Questionnaires including information on reproductive factors and lifestyle were completed by 269 healthy women, aged 40 years or younger. Body measurements and plasma prolactin levels were obtained during cycle days 5?10 and 18?23. Prolactin was higher in nulliparous than in parous women (P

Source: Familial Cancer, Vol. 7, No. 3. (2008), pp. 221-228.
Psychiatric Diagnoses in Historic and Contemporary Military Cohorts: Combat Deployment and the Healthy Warrior Effect: Am. J. Epidemiol., Vol. 167, No. 11. (1 June 2008), pp. 1269-1276.Rese arch studies have identified heightened psychiatric problems among veterans of Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF). However, these studies have not compared incidence rates of psychiatric disorders across robust cohorts, nor have they documented psychiatric problems prior to combat exposure. The authors' objectives in this study were to determine incidence rates of diagnosed mental disorders in a cohort of Marines deployed to combat during OIF or OEF in 2001-2005 and to compare these with mental disorder rates in two historical and two contemporary military control groups. After exclusion of persons who had been deployed to a combat zone with a preexisting psychiatric diagnosis, the cumulative rate of post-OIF/-OEF mental disorders was 6.4%. All psychiatric conditions except post-traumatic stress disorder occurred at a lower rate in combat-deploye d personnel than in personnel who were not deployed to a combat zone. The findings suggest that psychiatric disorders in Marines are diagnosed most frequently during the initial months of recruit training rather than after combat deployment. The disproportiona te loss of psychologicall y unfit personnel early in training creates a "healthy warrior effect," because only those persons who have proven their resilience during training remain eligible for combat. 10.1093/aje/kw n084Gerald Larson, Robyn Highfill-Mcroy , Stephanie Booth-Kewley

Source: Am. J. Epidemiol., Vol. 167, No. 11. (1 June 2008), pp. 1269-1276.
Projections of lung cancer mortality in West Germany: a case study in Bayesian prediction: Biostat, Vol. 2, No. 1. (1 March 2001), pp. 109-129.We apply a generalized Bayesian age-period-coh ort (APC) model to a data-set on lung cancer mortality in West Germany, in the period 1952-1996. Our goal is to predict future death rates until the year 2010, separately for males and females. Since age and period are not measured on the same grid, we propose a generalized APC model where consecutive cohort parameters represent strongly overlapping birth cohorts. This approach results in a rather large number of parameters, where standard algorithms for statistical inference by Markov chain Monte Carlo methods turn out to be computationall y intensive. We propose a more efficient implementation based on ideas of block sampling from the time series literature. We entertain two different formulations, penalizing either first or second differences of age, period and cohort parameters. To assess the predictive quality of both formulations, we first forecast the rates for the period 1987-1996 based on data until 1986. A comparison with the actual observed rates is made based on a predictive deviance criterion. Predictions of lung cancer mortality until 2010 are then reported and a modification of the formulation in order to include information on cigarette consumption is finally described. 10.1093/biosta tistics/2.1.10 9Leonhard Knorr-Held, Evi Rainer

Source: Biostat, Vol. 2, No. 1. (1 March 2001), pp. 109-129.
Age-period-coh ort models for the Lexis diagram: Statistics in Medicine, Vol. 26, No. 15. (2007), pp. 3018-3045.Anal ysis of rates from disease registers are often reported inadequately because of too coarse tabulation of data and because of confusion about the mechanics of the age-period-coh ort model used for analysis. Rates should be considered as observations in a Lexis diagram, and tabulation a necessary reduction of data, which should be as small as possible, and age, period and cohort should be treated as continuous variables. Reporting should include the absolute level of the rates as part of the age-effects.Th is paper gives a guide to analysis of rates from a Lexis diagram by the age-period-coh ort model. Three aspects are considered separately: (1) tabulation of cases and person-years; (2) modelling of age, period and cohort effects; and (3) parametrizatio n and reporting of the estimated effects. It is argued that most of the confusion in the literature comes from failure to make a clear distinction between these three aspects. A set of recommendation s for the practitioner is given and a package for R that implements the recommendation s is introduced. Copyright © 2006 John Wiley & Sons, Ltd.B Carstensen

Source: Statistics in Medicine, Vol. 26, No. 15. (2007), pp. 3018-3045.
Age?period?coh ort analysis of Swiss suicide data, 1881?2000: European Archives of Psychiatry and Clinical Neuroscience, Vol. 256, No. 4. (29 June 2006), pp. 207-214.Abstra ct At the end of the 19th century, male suicide rates in Switzerland were as high as the respective rates in recent decades, whereas female suicide rates were distinctly lower. An age?period?coh ort analysis was performed to provide more information about the genderspecific changes over the last century. Suicide mortality has been reported in Switzerland since 1876 when the standardised registration of mortality data began. The analysed data cover the period 1881?2000. The statistical analyses were based on log?linear models and data aggregated by 10?year age?intervals and 10?year periodinterval s. The results indicate similar age and period effects in males and females. The estimates representing age?specific risk increase steadily with age, with intermediate plateaus in the 20s and the 50s. The period?specifi c estimates follow the economic cycles. The birth cohort effects are stronger in males and weaker in females. In the males' estimates, there is a peak in cohorts born around 1840 and a low in cohorts born some 60?100 years later. The estimates increased again in generations born after World War II. In females, the birth cohort estimates are low in cohorts born in the first half of the 19th century and increase until the first half of the 20th century. Birth cohort effects remain an intriguing topic in epidemiology of suicide. A better understanding of birth cohort effects might open new doors to suicide prevention.V Ajdacic?gross, M Bopp, M Gostynski, C Lauber, F Gutzwiller, W Rössler

Source: European Archives of Psychiatry and Clinical Neuroscience, Vol. 256, No. 4. (29 June 2006), pp. 207-214.
Comments on ?Age-period-co hort models for the Lexis diagram? by Carstensen B. Statistics in Medicine 2007; 26:3018 -3045: Statistics in Medicine, Vol. 9999, No. 9999. (2007), n/a.No AbstractJoachi m Rosenbauer, Klaus Strassburger

Source: Statistics in Medicine, Vol. 9999, No. 9999. (2007), n/a.
The estimation of age, period and cohort effects for vital rates.: Biometrics, Vol. 39, No. 2. (June 1983), pp. 311-324.In models for vital rates which include effects due to age, period and cohort, there is aliasing due to a linear dependence among these three factors. This dependence arises both when age and period intervals are equal and when they are not. One solution to the dependence is to set an arbitrary constraint on the parameters. Estimable functions of the parameters are invariant to the particular constraint applied. For evenly spaced intervals, deviations from linearity are estimable but only a linear function of the three slopes is estimable. When age and period intervals have different widths, further aliasing occurs. It is assumed that the number of deaths in the numerator of the rate equation has a Poisson distribution. The calculations are illustrated with data on mortality from prostate cancer among nonwhites in the U.S.TR Holford

Source: Biometrics, Vol. 39, No. 2. (June 1983), pp. 311-324.
Do adolescent leisure-time physical activities foster health and well-being in adulthood? Evidence from two British birth cohorts: European Journal of Public Health, Vol. 16, No. 3. (June 2006), pp. 331-335.Sacker , Amanda, Cable, Noriko

Source: European Journal of Public Health, Vol. 16, No. 3. (June 2006), pp. 331-335.
Small-sample bias in synthetic cohort models of labor supply: Journal of Applied Econometrics, Vol. 22, No. 4. (2007), pp. 839-848.This paper investigates small-sample biases in synthetic cohort models (repeated cross-sectiona l data grouped at the cohort and year level) in the context of a female labor supply model. I use the Current Population Survey to compare estimates when group sizes are extremely large to those that arise from randomly drawing subsamples of observations from the large groups. I augment this approach with Monte Carlo analysis so as to precisely quantify biases and coverage rates. In this particular application, thousands of observations per group are required before small-sample issues can be ignored in estimation and sampling error leads to large downward biases in the estimated income elasticity. Copyright © 2007 John Wiley & Sons, Ltd.Paul Devereux

Source: Journal of Applied Econometrics, Vol. 22, No. 4. (2007), pp. 839-848.

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