Download Pregnancy hormones, symptoms, and coffee consumption

Applied Epidemiologic Analysis
Patricia Cohen, Ph.D.
Henian Chen, M.D., Ph. D.
Teaching Assistants
Julie Kranick
Chelsea Morroni
Applied Epidemiologic Analysis
Fall 2002
Sylvia Taylor
Judith Weissman
Lecture 12
Multiple time point assessments in
epidemiology: purposes, questions, and
analyses
GOALS:
To understand some of the reasons for longitudinal analysis in
epidemiology
To outline the circumstances in which a survival analytic
method, a Poisson regression method, a repeated measure
ANOVA method, a GEE method, or a multilevel method may be
selected
To understand the connection between multilevel methods for
clustered data and for longitudinal data in terms of the kinds
of questions that may be answered.
Applied Epidemiologic Analysis
Fall 2002
Epidemiology and longitudinal analysis
• In a sense all epidemiological analysis is longitudinal.
• Its goals are nearly always determination of potential causes
for which temporal priority is a necessity (all other analyses
being, in a sense, subsidiary to this goal).
• It has an emphasis on rates, which are intrinsically
longitudinal.
Applied Epidemiologic Analysis
Fall 2002
Matching data and analytic model
Data: Time to some event such as disease onset or diagnosis
Analytic choices depend on
– Whether you have exact person-time units for those who
do experience the outcome (disease) and for those who do
not experience it a time over which they were observed
before censoring (end of study, loss to follow-up, experience
of an incompatible outcome such as death)
– Sample size
– Appropriateness of a parametric assumption (e.g. shape of
time distribution)
– Proportion of the sample getting the outcome
Applied Epidemiologic Analysis
Fall 2002
Matching data and analysis (rate models)
Data include person-time for both cases and
referent participants (time to censoring)
Minimum
Parametric
cell N
Limit on
%
censored
Effect index
Life table
No
Yes
Yes
Curves/survival
rate
Kaplan-Meier
No
Yes
Yes
Curves/survival
rate
Cox regression
Semi
No
Yes
Hazard ratio
Poisson
regression
Yes
No
No
Log prob. change
Applied Epidemiologic Analysis
Fall 2002
Matching data and analytic model
(risk and change models)
Two time-point
data
Dependent variable
Effect Measure
Binary
Scaled
Yes
No
Odds change
Yes
No
Probability change
No
Yes
Unit change
GEE (logistic)
Yes
No
Repeat ANOVA
No
Yes
Multilevel
Yes
Yes
Logistic
regression
Probit
regression
OLS
Three + timepoints
Applied Epidemiologic Analysis
Fall 2002
Mean odds change
Mean difference
Mean change difference
Any of the above related to
mean DV and any desired
change function
Alternative longitudinal designs
A. Designs in which measurement of exposures, including
timing, are retrospective
B. Nested case-control studies with prospective measurement
of exposure and confounders and matched timing for cases
and controls
C. Cohort studies in which data on exposures are gathered
prospectively and disease outcomes are assessed in
subsequent follow-up
Applied Epidemiologic Analysis
Fall 2002
Retrospective studies
• Designs in which measurement of exposures, including
timing, are retrospective (gathered at a single time point in
case-referent and cross-sectional cohort studies), or based
on collection of pre-existing records.
• Accuracy of measurement is a problem, especially when it
is based on recall.
• When exposures or confounders are themselves timedependent or time-varying there can be considerable
problems in producing an unbiased estimate of exposure
effect. How will we know how much of the exposure is
attributable to the confounder and how much may have
preceded it?
• There may be effects of the exposure on a (partial)
confounder, or even of the disease influencing exposures
and/or confounders over time.
Applied Epidemiologic Analysis
Fall 2002
Nested case-control studies
One method of attempting to control at least some of these
problems:
– prospective measurement of exposure and confounders
– matched timing for cases and controls.
Applied Epidemiologic Analysis
Fall 2002
Longitudinal cohort studies
• Data on exposures gathered prospectively
• Disease outcomes gathered in follow-up
• In studies of disorders or conditions that change
over time, earlier disease status can be included
in the estimate of the effect of exposure on
persistence or new onset to ensure temporal
priority.
Disease2 =
B0 + BDDisease1 + BCConfounders1 + BEExposure1 + ε
Applied Epidemiologic Analysis
Fall 2002
Appropriate time intervals between measures
The biologically plausible period between the
exposure and disease needs to be taken into
account.
Applied Epidemiologic Analysis
Fall 2002
Frequently changing exposures, frequently recurrent
diseases, and varying biological indicators
When studying the relationship between variables that may
change over fairly short time periods, it is useful to include
more than two measurement points.
1. To inform about average changes in variables over time/ trials/
age
2. To improve inferences about the direction and magnitude of
influences of one variable or set of variables on another by
establishing sequence
3. To inform about individual or group differences in change over
time and variables that relate to these differences
Applied Epidemiologic Analysis
Fall 2002
Repeated assessments designed to inform about average changes
in variables over time/ trials/ age.
In the past these studies would often be analyzed by repeated
measure analysis of variance (ANOVA)
• Data collected for every study participant at each point in time
• Problems because of difficulties managing missing data and no
means of coping with variations in timing of assessments
Currently, these studies will almost invariably be analyzed with a
multilevel analysis program
• Missing data are readily handled, including “censored” data
• Timing of data collection can vary from participant to participant
• Depending on the number of time points included, the kinds of
questions about relationships of predictors to changes in
outcomes that can be addressed are substantially increased
• Time-varying predictors can be included in the analysis
• Autocorrelation can be included in the analysis
Applied Epidemiologic Analysis
Fall 2002
Repeated measures with binary outcomes
• One solution is analysis by Generalized Estimation
Equations:
• These models assume that in the population the correlation
between DV and predictors is constant over time and
provide overall estimates of DV effects under that
assumption.
• The other major solution is to employ logistic (or some
other link function appropriate for binary data) in multilevel
regression analysis.
Applied Epidemiologic Analysis
Fall 2002
Longitudinal analysis of changes in indices of
obesity from age 8 years to age 18 years
Dal S, Labarthe DR, Grunbaum JA, Harrist RB, Mueller WH.
2002. American Journal of Epidemiology, 156, 720-729.
Goals of study:
To examine growth patterns of obesity indices of
678 children studied at 4 month intervals for 4
years, beginning ages 8,11, and 14.
To compare these patterns for males and females
and for Black and White Children.
Applied Epidemiologic Analysis
Fall 2002
Figure 5. Sex- and race-specific trajectories of the sum of two
skinfold measurements
Applied Epidemiologic Analysis
Fall 2002
Lawson CC, LeMasters GK, Levin LS, Liu JH. 2002.
Pregnancy hormone metabolite patterns, pregnancy
symptoms, and coffee consumption. American Journal of
Epidemiology, 156, 428-437.
Goals of study
To determine relationships between:
1. Pregnancy hormone metabolites (PHM) & concurrent
coffee consumption (CC)
2. PHM and concurrent pregnancy symptoms (PS)
3. Pregnancy symptoms and coffee consumption
4. Pre-pregnancy coffee consumption and PHM
Applied Epidemiologic Analysis
Fall 2002
Study design
• Study subjects: 100 nonsmoking women enrolled on
average in the 6th week of pregnancy who had been prepregnancy coffee drinkers, recruited from advertising in
public and health service locations.
• Data collected retrospectively back to date of last menstrual
period and prospectively through week 12.
Applied Epidemiologic Analysis
Fall 2002
Pregnancy hormones, symptoms, and
coffee consumption
Applied Epidemiologic Analysis
Fall 2002
Pregnancy hormones, symptoms, and
coffee consumption
Analyses to answer study questions regarding
relationships between:
Pregnancy hormone metabolites (PHM) & concurrent
coffee consumption (CC)
-
Carried out by a multilevel analysis of the
relationship between weekly coffee consumption
(treated as DV) and (time-varying) PHM,
partialing pre-pregnancy coffee consumption and
smoking history. Two of three PHM were related
to current coffee consumption.
Applied Epidemiologic Analysis
Fall 2002
Pregnancy hormones, symptoms, and
coffee consumption
Other study findings determining relationships
between:
PHM and concurrent pregnancy symptoms (PS)
Weekly changes in these variables were strongly
related in multilevel models.
Nausea and appetite loss were not related to current
coffee consumption, but more vomiting was
associated with less coffee consumption.
Pre-pregnancy coffee consumption was related to
lower mean level of one of the pregnancy hormones
(a not anticipated finding).
Applied Epidemiologic Analysis
Fall 2002
Time-series analysis
• This set of techniques may be thought of as analogous to
ecological analysis of clustered data: they are studies of
changes in one unit over time.
• They are the backbone of econometric analyses and
equally relevant to the analysis of effects of changes in
public policy/ public health programs on aggregate public
health.
• The study we examined last week that looked at regional
differences in family planning policy and service availability
and regional differences in sexual activity and
contraceptive use by young women might have been a time
series if data pre and post policy/service changes had been
available.
Applied Epidemiologic Analysis
Fall 2002
Modeling changes in CD4+ T- Lymphocyte counts after the
start of highly active antiretroviral therapy and the relation
with risk of opportunistic infections
Binquet C, Chene G, Jacqmin-Gadda H, Journot V, Saves M,
Lacoste D, Dabis, F et al., American Journal of Epidemiology,
Question: Is there a minimal duration of CD4+ cell count
increase before its impact on opportunistic infection?
Design: 553 HIV patients treated with at least one protease
inhibitor and studied at least twice over the next months with
regard to CD4+ counts and opportunistic infection.
Applied Epidemiologic Analysis
Fall 2002
Evolution of CD4+ T lymphocity count among HIV+ patients on
antiretroviral therapy
Applied Epidemiologic Analysis
Fall 2002
Antiretroviral therapy and CD4+ counts
• Conclusions: There was a delay in the response to the
treatment over the first 4 months, including a delay in the
decline of rate of opportunistic infection and in the
relationship of CD4+ increase to this decline.
• After the fourth month, greater increase in CD4+ counts were
related to decline in opportunistic infection
• Unfavorable trend in CD4+ trend after four months is an
indication of drug failure and suggests therapy change.
Applied Epidemiologic Analysis
Fall 2002
TIME SERIES ANALYSES AND MULTILEVEL LONGITUDINAL
STUDIES
If a time series is based on aggregated data we may think of it
as comparable to ecological analyses with data only at the
clustered level.
If data are available both at the individual and aggregate level
we may still focus on the effects over time, using multilevel
analyses.
– Purposes and designs vary: May have designs that estimate
effects of service system or legislative policy change on health
indicators: Quasi-experimental designs may look at sudden
change in time-trends.
– As in clustered data, a major purpose may be to see whether
there are effects of “fixed” individual unit differences in the
relationship among variables including time. Is there a
difference in the slope (linear increase or decrease) of some
Applieddisease
Epidemiologicmarker
Analysis
over time associated with an exposure?
Fall 2002
Epidemiology of pertussis in a West African community before
and after introduction of a widespread vaccination program
• How did the vaccination program affect the incidence of
pertussis between 1984 and 1996 in an area within
Senegal?
• How did these effects impact children of different ages?
Applied Epidemiologic Analysis
Fall 2002
Pertussis in a West African community
Applied Epidemiologic Analysis
Fall 2002
Pertussis in a West African community
• Conclusion: periodic epidemics of pertussis were
dampened by vaccination.
Applied Epidemiologic Analysis
Fall 2002
Pertussis in a West African community: trends in age groups
Note that in contrast to the previous graph, these rates are per 1000, and
Applied Epidemiologic Analysis
differences
are smaller, numbers being partly due to decline in number of
Fall 2002
children.
Pertussis in a West African community
Conclusion: Age effects were larger among older children in the earliest
vaccinations, but were relatively equal among age groups thereafter.
Pertussis is a major cause of childhood morbidity and mortality globally.
Even among those who did not receive booster shots there was a decline
in mortality if there were subsequent infections.
There also appeared to be a herd immunity effect of vaccination, although
the level receiving even one dose was never much over 40%.
This study has data only at the aggregate level, and is thus rather like
ecological studies, without the ability to examine individual differences
(e.g. in number of vaccination doses effects or in the duration over which
immunity effects associated with specific numbers is effective).
Applied Epidemiologic Analysis
Fall 2002