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Perinatal Epidemiology Workshop
Russell S. Kirby, PhD, MS, FACE
Universi ty of Wisco nsin Medical School
As of July 2002:
Department of Maternal and Child HealthSchool o f Publ ic Health
Univers i ty of A labama-Birm ingham
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Objectives
Focus on components of infant mortality
Review the theoretical basis for conventionally usedmeasures (neonatal, postneonatal)
Evaluate the utility of these measures with population-based data
Consider alternative methodologies foroperationalizing these measures
Propose study designs to test alternative measures inrelation to conventional measures
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TOP TEN LIST
TEN BEST WAYS TO MISUSECONFIDENCE INTERVALS
With apologies to David Letterman, and thanks for editorial assistance to
Elizabeth Kirby and for their insights to the following Internet contributors:
Patrick Remington, University of Wisconsin Medical School
Robert Meyer, N.C. Birth Defects Monitoring Program, State Center for Health
Statistics
N.C. Division of Public Health
Richard Miller, Wisconsin Bureau of Health Information
Russel Rickard, Colorado Responds to Children with Special Health Needs
Kim Hauser, University of South Florida
R.S. Kirby, March 2002
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"If the confidence interval is verytight, the case for causation isstrengthened...."
Submitted without attribution as a quotation from a
manuscript under review by
Patrick Remington
University of Wisconsin Medical School
February 24, 2002
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Being a statistician means never having to
say you're wrong. Don't be afraid to use
those 100% CIs so that you can state with
authority:
"I'm 100% sure that the true populationparameter lies between zero and infinity!"
Number 10
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
Say It With Total Confidence
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Whether you calculated the CIs or not, it isnt
necessary or desirable to include them in your
publication.
A general statement in the text to the effect that
all statistical values were significant should
be sufficient for all but lay audiences.
Number 9
Out of Sight, Out of Mind
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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Assess statistical significance through visual
comparison of confidence intervals.
For example: which of the following confidence
intervals is larger?
OR >-------
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Number 7
Smoke and Mirrors
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
On a graph, overly wide confidence bands can be
adjusted by plotting the data on an arithmetic
scale and the CIs on a logarithmic scale.
Your friends will be amazed at how tight those CIs
become.
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Remember that any results would have been
statistically significant if only your sample size
was large enough. This should not ruin otherwise
good science.
To compensate for small sample sizes, adjust your
CIs so that the null value is always
excluded. Don't be afraid to use 15% CIs if
necessary, if that will help support your
hypothesis.
Number 6
How Big is Your N?
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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Never include your point estimate within the
confidence limits.
When questioned, blame it on the computer
program.
Number 5
To Really Foul Things Up . . .
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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Number 4
Will 99 and a Half Do?
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
95% CIs are trite and commonplace. Be
creative Try reporting results such as the2log(67.45%) CIs and see what exciting results
you get.
No one will understand it, but they dontunderstand the 95 or 99% CIs either.
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Selectively quote the results concerning one
confidence limit. For example, when the estimate
of the confidence interval is 0 to 70, perhaps for
the association between watching late night
reruns and sleep disorders:
This risk factor decreases the risk of the
outcome up to 70%.
Number 3
Sound Bytes Are Best
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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To demonstrate statistical significance for a
comparison of rates or proportions, visually examine
the two confidence intervals.
Try comparing the lower confidence bound of the
smaller value with the upper confidence bound of the
larger value. If that still doesnt work, try fitting ever
narrowing confidence bands (e.g. the 15% CIs as inNumber 6 above) until the confidence limits no longer
overlap.
Number 2
Why Infer When You Can Guess?
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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The best way to do misuse confidence
intervals is to confuse statistical significancewith true, substantive significance.
An observed statistical difference begs the
question So what? which is too seldomasked.
Number 1
Is That All, Folks?
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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If you pay strict attention to these
suggested methods for using confidence
intervals, you too can misuse confidence
intervals with confidence.
-- R. S. Kirby
March 25, 2002
Top Ten List: Ten Best Ways to Misuse Confidence Intervals
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Brief Summary for Those Who Are Knitting, Doin
Crossword Puzzles, or Discerning the Geometric
Pattern in the Carpeting
Too often in public health, we use measures and present data in
familiar forms because thats the way weve always done it.
The concepts underlying measures of neonatal and postneonatal
mortality have their origins in sociological theory from the period
1880-1940. Periodically our indicators and outcome measures need to be
reviewed for contemporary validity (especially construct validity).
Some alternatives (for infant mortality classifications) include more
careful consideration of underlying causes of death, more
sophisticated record linkages, and developmental measures.
This is fertile ground for innovative, multidisciplinary research.
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Resource
Kirby, Russell S., "Neonatal and
Postneonatal Mortality: Useful Concepts or
Outdated Constructs?", Journal ofPerinatology, 13,6 (November-December
1993), 433-441.
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Historical Context
Neonatal and postneonatal mortality developed as
as demographic measures
Proxies for general categories of cause of infant
death
Endogenous causes (perinatal, congenital and
immediate newborn period)
Exogenous causes (nonperinatal infection, injury,homicide, other external causes)
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Conventional Wisdom
Deaths occurring early in the first year of life aremore likely associated with endogenous causes
Deaths after the early part of infancy are more
likely associated with endogenous causes (socio-economic or standard of living)
Since the 1940s, we have continued to defineneonatal mortality as deaths in the first 27 days of
life, and postneonatal mortality as deaths in thebalance of the first year of life
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Whats Happened Since 1940
Secular decline in infant mortality rates
Since the 1970s, a more rapid decline in neonatalmortality rates
Prior to about 1985, much of this decline resulted inpostponement of death into the postneonatal period
More recently, technological advances and improvements inneonatal resuscitation and NICU management have led to greaterrelative declines in neonatal mortality
In the 1990s, some health promotion programs have beensuccessful in targeting SIDS, a condition that occurs primarily inthe postneonatal period
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Neonatal and Postneonatal Mortality Rates
United States, 1960 - 1999
26.024.7
20.0
16.1
12.610.6
9.2 7.6 7.1
0
5
10
15
20
25
30
1960 1965 1970 1975 1980 1985 1990 1995 1999
Infant Neonatal Postneonatal
Rate per 1,000 live births
Source: National Center for Health Statistics, final mortality data
Prepared by March of Dimes Perinatal Data Center, 2002
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Methods for the Useful Constructs Study
Information on deaths from linked birth and infantdeath certificates
Underlying causes of death classified into
endogenous and exogenous causes Mortality rates compared within birth weight
strata between endogenous and neonatal andbetween exogenous and postneonatal mortality
rates
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The Bottom Line
At least in the 1980s, neonatal and endogenous mortalitymeasures are fairly synonymous
Postneonatal mortality is no longer a useful proxy forexogenous infant mortality
This renders the conventional classification suspect forcurrent purposes
New on the scene are advances in perinatal-infant medicineand nursing management, the new ICD-10 classification fordiseases, and more readily available data resources throughrecord linkage, chart review, and other data acquisitionmethods
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Future Studies?
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Three Alternative Formulations:
One
Use conventional definitions, but calculate
neonatal and postneonatal mortality rates bases on
corrected gestational age
Thus, a term neonate who dies during the first monthafter birth is a neonatal death
A 32 week infant who dies prior to the 12th week of
life (40-32=8 + 4 weeks of conventional neonatal
period) is considered a neonatal death
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Three Alternative Formulations:
Two
Include fetal deaths in the analysis, regarding all
of these events as non-postneonatal.
Conduct the analysis conventionally, or use the
corrected gestational age definition
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Three Alternative Formulations:
Three
Incorporate linked birth-infant death certificate and infant
hospital discharge records into the analysis
Define neonatal and postneonatal in relation to initial
continuous hospital stay. Example: a baby born at one hospital who is transferred to an
NICU at another hospital and is discharged at 9 weeks has a
neonatal period lasting 63 days.
Another example: a healthy newborn is discharged on the
second postpartum day, and has a neonatal period lasting 2 days
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Three Alternative Formulations:
Three (continued)
Use the person-days method for calculating rates.
Thus, the neonatal mortality rate is the number of
neonatal deaths according to this definition,
divided by the total number of initial newbornstay days. The postneonatal mortality rate is the
number of non-neonatal infant deaths, divided by
the balance of lived postneonatal days.
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However beautiful the strategy, you
should occasionally look at the
results.
-- Sir Winston Churchill
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Critique of Alternatives
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Critique of Alternatives
Corrected gestational age will only work when
gestation is measured accurately. That is a topic
for at least another workshop if not an entire
MCH epidemiology conferencebut allowing forsome error at early gestational ages its worth a try
All of the problems with birth certificate and
infant death certificate data quality are at least an
order of magnitude worse with fetal death records
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Critique of Alternatives
Hospital discharge databases are becoming more widelyavailable. However, in most states these files are not linked inthe manner necessary to support the proposed analysis.
Most public health professionals and demographers are
unfamiliar with rates expressed as person-time measures
A validated measure for neonatal and postneonatal mortalitycould serve as the basis for more careful multivariate analyses,
but first its validity and reliability must be independently
verified For the time being, it is likely we are stuck with the same old
same old.
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Questions?
Im interested in hearing from you!
I can be reached by e-mail at
414-219-5610, FAX 414-219-5201
Ill provide forwarding information atthese locations after July 2002
mailto:[email protected]:[email protected]:[email protected]:[email protected]