Interpreting age, period and cohort effects in plasma lipids and serum insulin using repeated measures regression analysis: the CARDIA study

Jacobs, David R.; Hannan, Peter J.; Wallace, Dennis; Liu, Kiang; Williams, O. Dale; Lewis, Cora E.

doi:10.1002/(sici)1097-0258(19990330)18:6<655::aid-sim62>3.3.co;2-l

Cited by 12 publications

(15 citation statements)

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“…The varying effects of age are introduced to the analysis in a continuous form. However, in the longitudinal data analysis, the age effect is confounded with period and cohort effects, and this interference needs to be considered in the analysis 25. There was a recession in the early 1990s, which resulted in adverse economic trends 26.…”

Section: Methodsmentioning

confidence: 99%

Health selection operating between classes and across employment statuses

Ki¹,

Sacker

Kelly

et al. 2010

Journal of Epidemiology & Community Health

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The non-significant impact of health on mobility inside employment may reflect the presence of the significant impact of health on mobility between employment and non-employment. This implies that the effect of health was not evenly spread over all social mobility, but rather tends to concentrate on some types of mobility. The effect of each predictor on social mobility is more concentrated among specific transitions, and health and age were likely to be substantial in moving into/out of the labour force, whereas education was a relevant predictor for mobility into/out of upper classes, in particular, classes I/II.

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Section: Methodsmentioning

confidence: 99%

Health selection operating between classes and across employment statuses

Ki¹,

Sacker

Kelly

et al. 2010

Journal of Epidemiology & Community Health

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“…Both follow up studies of single age cohorts and studies of cross sectional differences are based on two time points at most, 14 15 20-24 and so complicate the separation of the effects of aging, period, and birth cohort. 25 Even given suitable data, there is the additional difficulty of social mobility to consider. At any time point, a social class group will include people who have previously spent time in more or less advantaged classes, as well as those who have always been in that class.…”

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confidence: 99%

“…A GCM is characterised by repeated measures of a dependent variable as a function of time and other covariates. GCM are suitable because they can be used to separate the effects of aging, period, and cohort, 25 and social position can be specified as a time varying influence. Other applications of growth curve models include the acquisition of educational skills, physical weight and height trajectories, the development of substance use, and poverty experiences and health.…”

mentioning

confidence: 99%

Social dynamics of health inequalities: a growth curve analysis of aging and self assessed health in the British household panel survey 1991–2001

Sacker

Clarke²,

Wiggins³

et al. 2005

J Epidemiol Community Health

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Objectives: To study how social inequalities change as people age, this paper presents a growth curve model of self assessed health, which accommodates changes in occupational class and individual health with age. Design: Nationally representative interview based longitudinal survey of adults in Great Britain. Setting: Representative members of private households of Great Britain in 1991. Participants: Survey respondents (n = 6705), aged 21-59 years in 1991 and followed up annually until 2001. Main outcome measure: Self assessed health. Results: On average, self assessed health declines slowly from early adulthood to retirement age. No significant class differences in health were observed at age 21. Health inequalities emerged later in life with the gap between mean levels of self assessed health of those in managerial and professional occupations and routine occupations widening approaching retirement. Individual variability in health trajectories increased between ages 40 and 59 years so that this widening of mean differences between occupational classes was not significant. When the analysis is confined to people whose occupational class remained constant over time, a far greater difference in health trajectories between occupational classes was seen. Conclusions: The understanding of social inequalities in health at the population level is enriched by an analysis of individual variation in age related declines by social position.

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“…The values obtained using these equations with a projected exhalation time of 8 seconds approximated the predicted values published by Hankinson et al (13). We previously reported a trend in FVC and FEV 1 over spirometric examinations at years 0, 2, 5 and 10, based on a mathematical technique of looking at differences in these measures in people of the same age assessed at different examinations (15). We added 53 ml, 54 ml, and 16 ml to the predicted FVC at year 0, 2, and 5, respectively (10).…”

Section: Discussionmentioning

confidence: 99%

Spirometry guidelines influence lung function results in a longitudinal study of young adults

Smith

Arynchyn

Kalhan

et al. 2010

Respiratory Medicine

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Rationale End of test criteria can influence spirometry results. Epidemiology studies initiated before adoption of the 1987 American Thoracic Society (ATS) guidelines typically used a 1 or 2 second plateau on the volume-time curve, not a minimum test duration of 6 seconds, to terminate a test. Objectives To determine the effect of changing guidelines on FEV1, FVC and FEV1/FVC during a longitudinal study of young adults. Methods Spirometry was performed on participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Values obtained at entry and 2, 5 and 10 years later using accepted procedures were re-evaluated using the 2005 ATS-ERS guidelines, which were in effect for the year 20 exam. Generalized estimating equations were used to adjust tests with short exhalations that were acceptable by then current end of test criteria. Results The percentage of participants at years 0, 2, 5, and 10 with exhalations less than six seconds but with an acceptable plateau was 33%, 29%, 9%, and 2%, respectively. Exhalations less than 6 seconds occurred more frequently in younger and female participants, and were associated with lower FVC and higher FEV1/FVC. For short exhalations the adjusted FVC was 47 ml and 110 ml higher than the measured FVC when 6 and 8 second exhalation times were used. Conclusions In longitudinal studies of young adults, changing end of test criteria may affect lung function, especially among younger and female participants. Determining adjusted values for tests with short exhalations may better represent the lung health of participants.

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Interpreting age, period and cohort effects in plasma lipids and serum insulin using repeated measures regression analysis: the CARDIA study

Cited by 12 publications

References 0 publications

Health selection operating between classes and across employment statuses

Health selection operating between classes and across employment statuses

Social dynamics of health inequalities: a growth curve analysis of aging and self assessed health in the British household panel survey 1991–2001

Spirometry guidelines influence lung function results in a longitudinal study of young adults

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