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State Example: Translating Infant Mortality Toolkit Content• This slide set, provided by Elizabeth J Conrey, PhD, RD, is an example of
how the content from the Infant Mortality Toolkit can be translated for training public health practitioners
• The slides are a subset from the course titled: The Epidemiology of Maternal and Infant Health for State and Local Practitioners, given at the Ohio State University Summer Program in Population Health
• Examples provided are from the Ohio Department of Health
State Example: Translating Infant Mortality Toolkit Content
Content from Day 1 - Toolkit Chapters Addressed: • Why Focus on Infant Mortality
• Using U.S. data, the slides outline trends, racial/ethnic disparities, and geographic disparities in infant mortality
• For Those Just Starting - Standing on Common Ground: Data Sources, Definitions, Basic Calculations• Using U.S. and Ohio examples, the slides describe key sources of
data to examine infant mortality, definitions integral to feto-infant mortality, measures of occurrence, measures of association, and methods of determining statistical significance
The Epidemiology of Maternal and Infant Health for State and Local PractitionersElizabeth J Conrey, PhD, RD
June 22-26, 2015
The Ohio State University, 2015 Summer Program in Population Health
Why Focus on Infant Mortality?
Measure of population health and health care
Recognized as crude indicator of: Community Health Status
Poverty and SES in a community
Availability and quality of health services and medical technology
Wide acceptance of measure
Easily calculated
Common use in needs assessments and evaluation
ODH Priorities for Improved Health
VISIONOptimal health for all Ohioans
MISSIONProtect and improve the health
of all Ohioans by preventing disease, promoting good health,
and assuring access to quality care
U.S. Trends in Infant Mortality,
1915-1997
US Trends in Infant Mortality, 1997-2013
199719981999200020012002200320042005200620072008200920102011201220130
2
4
6
87.2 7.2 7.0 6.9 6.8 7.0 6.8 6.8 6.9 6.7 6.8 6.6 6.4 6.2 6.1 6.0 6.0
199719981999200020012002200320042005200620072008200920102011201220130
2
4
6
87.2 7.2 7.0 6.9 6.8 7.0 6.8 6.8 6.9 6.7 6.8 6.6 6.4 6.2 6.1 6.0 6.0
Remember to see the faces behind the numbers…
--William Foege
US Trends in Infant Mortality, 1997-2012
Low & Very Low Birth Weight, US, 1990-2012
Racial & Ethnic Disparities in US IM
Geographic Disparities in Infant Mortality, by State– US, 2010
Standing on Common Ground: Data Sources, Definitions, Basic Calculations
Maternal & Infant Data Sources & Systems
NS-Childrens Health FIMR NS-
CSHCNBirth
Defects
PRAMS BRFSS Maternal Mortality
Vital Records
Medicaid
Oral Health WIC Newborn
Screening
Hospital Discharge
Child Fatality Review STD OMAS
Ohio
Maternal & Infant Data Sources & Systems
NS-Childrens Health FIMR NS-
CSHCNBirth
Defects
PRAMS BRFSS Maternal Mortality
Vital Records
Medicaid
Oral Health WIC Newborn
Screening
Hospital Discharge
Child Fatality Review STD OMAS
Ohio
Data Sources: National Data Only
Ohio
National Hospital Care Survey (NHCS)
National Health and Nutrition Examination Survey (NHANES
Data Sources: National and all States/Regions
Ohio
National Vital Statistics (NCHS) Live Births
Infant Deaths
Fetal Deaths
Linked Birth/Death files
National Immunization Survey (NIS)
National Survey of Children’s Health (NSCH)
National Survey of Children with Special Health Care Needs
Data Sources: National & Regions
Ohio
National Survey of Family Growth (NSFG)
National Health Interview Survey – Child (NHIS)
Data Sources: State Specific (all states)
Ohio
State Department of Health Vital Statistics Live Births
Infant Deaths
Fetal Deaths
Linked Birth/Death files
Behavioral Risk Factor Surveillance System
Hospital Discharge
Medicaid Claims
WIC Participant Characteristics (USDA)
Data Sources: State Specific (select)
Ohio
Health Care Utilization Project (HCUP), AHRQ
Youth Risk Behavioral Surveillance System (YRBSS)
PRAMS
School Health Profile Surveys
Birth Defects Registry Ohio Connections for Children with Special Needs (OCCSN)
Child Fatality Review
Perinatal Quality Care Collaboratives Vermont Oxford Network (VON)
Maternal Mortality Review Pregnancy Associated Mortality Review (PAMR)
Emergency Medical Services (EMS)
Data Sources: State/Local Health Social Service Programs
Ohio
WIC
Family Planning
Home Visiting Programs
Hospital and Insurance Records
Ohio Medicaid Assessment Survey (OMAS)
Data Sources: Local Review Programs
Ohio
FIMR Age at death
Cause of Death
Maternal & Infant Data Sources & Systems
Ohio
Vital Records
Jurisdiction Responsibility for Vital Event Registration
ALL vital events that occur within each of the 57 jurisdictions (50 states, NYC, DC, 5 territories):• Live births
• Deaths
• Fetal deaths (based on length of gestation/birth weight)
• Induced Terminations of Pregnancy (ITOP)
• Marriages and Divorces
Early Vital Statistics Registration
Registration within parishes, ensured legal rights (≤ 1632 in Virginia)
Need for registration not in the Constitution Shifted from
church recording of traditional events: christenings, marriages, burials
Shifted to government recording of vital events: births, deaths,
marriages To collect and preserve records not for statistical purposes, but
legal evidence (e.g., property inheritance)
Early US Registration Systems
Cities were first: Boston, NYC, Philadelphia, Baltimore, New Orleans (1833)
Massachusetts first state system (1842) US government started to develop and maintain
a uniform system of registration after the 1900 census (last state was Texas, added in 1933)
Welfare and old age legislation of 1930s and World War II resulted in birth certificates becoming much more important for legal documentation
Early Ohio Death Registration
1867 Cincinnati
1870s Cleveland, Dayton
1880s Chillicothe, Nelsonville, Salem, Warren
1890s 16 cities, including Mansfield, Youngstown, Marietta, Springfield
1900s 22 cities, including Columbus, Akron, Canton, Toledo
Ohio VS Registration: 1908 Ohio passed Vital Statistics Registration Act
Considered model legislation , based on APHA VS section work
1,150 registration districts! (down to 118 in 2011)
Estimated 100% complete death reports, 80% complete birth reports in 1909
Ohio VS Registration: 1908
1908 Ohio passed the Vital Statistics Registration Act
Considered the model legislation of the time, based on APHA VS section work
1,150 registration districts! (down to 118 in 2011)
Estimated 100% complete death reports, 80% complete birth reports in 1909
From Records to Statistics
Use of birth and death records for control of epidemics and to improve sanitary conditions
Cholera in Europe and America (1830’s) Chadwick and Farr (Europe) and Shattuck
(Massachusetts) Comparative infant mortality statistics to
prove life-saving value of milk pasteurization 1898: first disease classification system for
deaths
Two Purposes of Vital Records
Legal/administrative uses (civil registration)
• Proof of citizenship, age, parentage
• Used to obtain identity documents, settle estates, obtain benefits
Public health/statistical uses
• Measure outcomes
• Identify risk factors
• Conduct research
National Center For Health Statistics (NCHS)
Established by law, NCHS is federal government’s principle health statistics agency
Through shared relationships and contracts with 57 jurisdictions (50 states, 2 cities, and 5 territories), NCHS responsible for disseminating nation’s official vital statistics
Jurisdictions are responsible for maintaining registries of vital events and issuing copies of birth, marriage, divorce, and death certificates.
www.cdc.gov/nchs/nvss.htm
Ohio VS receives from NCHS…
NCHS also collects, analyzes, and disseminates health statistics that provide national & state comparisons for Ohio
Limited monetary support Guidance and technical assistance on data:
- collection, storage, standards, & procedures
- processing methodologies
- coding, editing
- transmissions to NCHS
Process for Registering Vital Events and Preparing Data for Release
• Many steps
• Many actors
• Complex systems
• Differs by type of event
• Multiple data quality reviews
• National data depend on slowest jurisdiction
Vital Records Data
Natality data: From the birth certificate.
Mortality data: From the death certificate. Date of birth distinguishes infant deaths.
Linked birth-infant death records: Linkage and merging of birth certificate and death certificate data.
Induced Abortions
Fetal Deaths
Ohio Vital Statistics: Live Birth Variables
Ohio
Infant Variables
Maternal Variables
Paternal Variables
Data Warehouse Functionality Available
http://www.odh.ohio.gov/healthstats/dataandstats.aspx • Downloads• Charts• Reports• Maps• Data View (with Query)• Secure and Public Versions• Population-based rates (Cancer module only)
Vital Statistics Warehouse Dataset Status
COMPLETED• Resident Live Births • Occurrence Live Births• Deaths• “Added Value” Modules
DEFINING REQUIREMENTS / BUILDING• Fetal Deaths• “Added Value” Modules
Maternal & Infant Data Sources & Systems
PRAMS
Guest Presenter: Missy Vonderbrink, MPHMCH EpidemiologistOhio Department of Health
Maternal & Infant Data Sources & Systems
Ohio
FIMRChild
Fatality Review
Ohio Child Fatality Review
Ohio
FIMR Age at death
Cause of Death
Ohio Fetal Infant Mortality Review
Ohio
Overarching Goal provide community leaders with recommendations from case reviews
Ohio FIMRs Cincinnati since 2008
7 New beginning 2014/15
Columbus/Franklin
Cuyahoga
Cleveland (expanding)
Butler
Lucas/Toledo
Stark/Canton
Summit
DEFINITIONS
Conception Live Birth 1 Year
Gestation Infancy20 wks 28 days
Fetal Death Infant Death
Neonatal Death
Reported Vital Events
Postneonatal Death
Feto-Infant Death
28 wks
Perinatal Death #1
7 days
Perinatal Death #2
1
2
Conception Live Birth 1st Birthday
Gestation Infancy20 wks 28 days
Fetal Death Infant Death
Neonatal Death
Definitions: Reported Vital Events
Perinatal Death
Postneonatal Death
Feto-Infant Death
12
4
5
3
6
Annual Infant Mortality Rate
Deaths in year= --------------
Births in yearX 1,000
SAMPLE PROBLEMIn 2012, 138,284 babies were born alive in Ohio and in the same time period, 1047 infants died before reaching their first birthday. What was the infant mortality rate for Ohio?
Deaths--------------
BirthsX 1,000 =
1047
-------------- 138,284
7.57
Infant Mortality Has 2 Main “Subcomponents”
# infant deaths between 0-27 days of life for a defined time period
= -------------- Births in same time
period
X 1,000
Neonatal Postneontal
# infant deaths between 28 and 365 days of life for a defined time
period
= -------------- Births in same time period
X 1,000
Infant Deaths by Age at Death, Ohio, 2012
Postneonatal 31%
Neonatal 69%
Neonatal Postneonatal Total0
2
4
6
8
5.21
2.36
7.57
Rate
per
10
00
liv
e b
irth
s
HP2020
Gestational Age and Preterm Birth Measures
Very preterm
Gestational age The age of the fetus or newborn infant in weeks
Estimates of a newborn’s gestational age based on birth certificate data are used to monitor trends in birth health
Late Preterm
image credit Wikipedia
Gestational Age and Preterm Birth Measures
Term birth: live births between 37 and 41 completed weeks gestation between 37 and 38 weeks referred to as Early Term
Preterm birth: live births less than 37 completed weeks (<259 days)
Very Preterm birth: live births less than 32 completed weeks Late Preterm birth: live births between 34 and 36 completed
weeks
Preterm Birth Rates, Ohio & US, 2001-2013
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 20148
9
10
11
12
13
14
*
//
Ohio
US
*preliminary
Percentage of Infants Born Late Preterm, by State, US 2012
NCHS
Birth Weight Measures
# live births weighing <2,500 g
= ---------------- # live births in same time
period
Low Birth Weight (LBW) RateVery LBW
<1,500 g
Moderately LBW 1,500 – 2,499 g
Low Birth Weight
Highly correlated with gestational age
Lower the birth weight the greater the risk for poor outcomes
LBW babies 25x more likely to die in 1st year of life
VLBW babies 100x more likely to die in 1st year
Low Birth Weight Rates Ohio & US, 2001-2013
19901992
19941996
19982000
20022004
20062008
20102012
0
2
4
6
8
10
Ohio
United States
Low Birth Weight (<2500g) Singleton Births, by Race/Ethnicity, Ohio, 2010-2012
Hispanic Black White0
2
4
6
8
10
12
14
16
Percent of Low Birth Weight Births by State and County– US, 2011 & Ohio, 2010-2012
Fetal Death Measures
“Death prior to the complete expulsion or extraction from its mother of a product of human conception, irrespective of the duration of pregnancy and which is not an induced termination of pregnancy”
Reporting Requirements (Ohio and most states) 20 weeks gestation or greater
“Death is indicated by the fact that after such expulsion or extraction, the fetus does not breathe or show any other evidence of life, such as beating of the heart, pulsation of the umbilical cord, or definite movement of voluntary muscles. Heartbeats are to be distinguished from transient cardiac contractions; respirations are to be distinguished from fleeting respiratory efforts or gasps.”
Fetal Death Measures
Early fetal death: A fetal death between 20 and 27 weeks of gestation.
Late fetal death: A fetal death at or after 28 weeks of gestation.
Perinatal Measures
Perinatal I
Refers to around (peri) the time of birth (natal) The entire or parts of the period beginning before conception and through the
first year of life
# fetal deaths >20 weeks gestation + infant deaths <28 days of life
= -------------- births plus fetal deaths
in same time period
X 1,000
Perinatal II
# fetal deaths >28 weeks gestation + infant
deaths <7 days of life
= -------------- births plus fetal deaths
in same time period
*NCHS definitions
X 1,000
Perinatal Mortality*, Ohio 2003-2012
2003 2004 2005 2006 2007 2008 2009 2010 2011 20120
1
2
3
4
5
6
7
8
9
10
7.27 6.94 7.04 6.97 7.01 6.996.56
6.977.39 7.33
Year
Rate
per
1,0
00
Liv
e B
irth
s
an
d F
eta
l D
eath
s
* NCHS Perinatal definition I: Fetal deaths of 28 weeks gestation or more and infant deaths of less than seven days of age.
BASIC CALCULATIONS
BASIC CALCULATIONS: Measures of Occurrence
Infant Mortality Rate
Cause-Specific Infant Mortality Rate
Proportionate Mortality Rates
Cause Specific Infant Mortality Rate
number of deaths from cause
(born in [birth year/s])= --------------------
births in yearX 100,000
Cause Specific Mortality: Ohio, 1990-2011
199519961997199819992000200120022003200420052006200720082009201020110
50
100
150
200
250Preterm Related Obstetric Complications
Maternal complications of pregnancy Congenital Anomalies
SIDS
Rat
e pe
r 10
0,00
0 B
irth
s
Proportionate Mortality Rate
number of deaths from cause
(born in [birth year/s])= ------------------------------- total number of deaths from all causes (in [birth
year/s])
X 100
BASIC CALCULATIONS: Measures of Occurrence – Standardized Rates
Direct Method
Indirect Method
Standardized Rates: Direct Method
Direct Adjusted Rate (DAR) Formula
m
Σ ci * ri i
m = number of strata
i = stratum
c = proportion of standard population in stratum i
r = rate in study population in stratum i
EXAMPLEStandardized Rates: Direct Method
Age (in years)Strata
(i)
US Birth Population
(c)
“STATE” Birth Population
US Infant Mortality
Rate/ 1,000 Live Births
“STATE” Infant
Mortality Rate / 1,000 Live Births
<18
18-20
21-34
35-44
TOTAL 100% 100%
Standardized Rates: Indirect Method
Used when insufficient data to directly calculate observed number
of infant deaths = --------------------- expected number
of infant deaths
X 100
Standardized Mortality Ratio (SMR)
EXAMPLE: Indirect Method
Birth WeightStrata
(i)
Live Births Ohio(c)
US Infant Mortality
Rate(r)
Expected Deaths
Observed Deaths
500-999 g
1,000-1,499 g
1,500-1,999 g
2,000-2,499 g
TOTAL
CASE STUDY Florida analyzed vital records data to identify geographic areas
where low birth weight and infant mortality rates were statistically higher than expected after adjusting for race, marital status and education level. Florida used an indirect method to calculate adjusted rates. This analysis informed further analysis and helped the Department of Health to focus efforts in counties that had significantly higher than expected infant deaths and low birth weight births.
For further detail, see information provided in the link:
www.doh.state.fl.us/Family/mch/docs/infant_mortality_docs/ExpectedRatesByCounty09.pdf
BASIC CALCULATIONS: Measures of Association (comparing rates)
Relative Risk of Infant Death
Absolute Risk Difference of Infant Death (Excess Death Rate)
Relative Risk of Cause-Specific Infant Death
Absolute Risk Difference of Cause-Specific Infant Death (Excess Cause-Specific Death Rate)
Measures of Association: Relative Risk of Infant Death
preferred for etiological studies of association
controls for baseline differences in mortality rates when comparing a risk factor across groups, time periods or outcomes
number of live
births among infants (group a)
number of live births among
infants (group b)
number of deaths among
infants (group a)
number of deaths among infants
(group b)
Measures of Association: Absolute Risk Difference of Infant Death
Excess rate
preferred for identifying potential to prevent a poor outcome or disease and quantifying the actual numbers in the population affected
number of
deaths among infants (group b)
X 1,000
number of live-born infants
(group b)
number of deaths among
infants (group a)x 1,000
number of live-born infants
(group a)
Measures of Association: Relative Risk of Cause-Specific Infant Death
For example, to compare deaths due to SIDS in one time period to another, or among one racial group to another
number of live
births among infants (group a)
number of live births among
infants (group b)
number of deaths from cause A
among infants (group a) x 1,000
number of deaths from cause A
among infants (group b) X 1,000
Measures of Association: Relative Risk of Cause-Specific Infant Death
Ohio 2011 preterm-related deaths among black (a) and white (b) births
= 3.89
3.785
0.972
Measures of Association: Absolute Risk Difference of Cause-Specific Infant Death
Excess Cause-Specific Death Rate number of
deaths from Cause B among infants (group b)
X 1,000
number of live-born infants
(group b)
number of deaths from
cause A among infants (group a)
x 1,000
number of live-born infants
(group a)
Measures of Association: Absolute Risk Difference of Cause-Specific Infant Death
Ohio 2011 preterm-related deaths among black (a) and white (b) births
= 2.812 0.9723.785
If black infants had the same mortality rate as white infants, 65 more black infants would have lived in 2013
EXAMPLE: Cause-Specific Attributable Risks2008-10
NHB2008-10
NHW
Excess Cause-Specific Death Rate
Cause-Specific Proportion of Excess Deaths
Cause-Specific Infant Mortality Rate (per 1,000) (Ai-Bi) (Ai-Bi) / (Σ Ai-Σ Bi)
Preterm or LBW -related 3.2 1.3 1.9 23.8%
Congenital anomalies and chromosomal
abormal.1.5 1.2 0.3 3.7%
SIDS 2.3 0.6 0.7 8.8%
Maternal complications of pregnancy 0.9 0.5 0.4 5.0%
Complications of placenta, cord and
membranes0.8 0.4 0.4 5.0%
Other 5.6 2.3 3.3 41.3%
TOTAL 14.3 6.3 8.0 100%Franklin County Health Indicator Brief: Trends 1990-2010 Infant Mortality
100
BASIC CALCULATIONS: Testing the significance of differences
Differentiate
statistically significant
~versus~
clinically or programmatically meaningful
EXAMPLE: statistically significant vs. meaningful differences
1. U.S.- Very Low Birth Weight (VLBW) Deliveries
n %
1996 53,425 1.4
2008 61,773 1.5
P<0.05
2. County A - Very Low Birth Weight (VLBW) Deliveries
n %
1996 44 1.1
2008 110 2.2
P>0.05
BASIC CALCULATIONS: Methods for determining statistical significance
Using Confidence Intervals to Determine Statistical Significance
Using the Standard Error for Determining Statistically Significant Differences Between Two Rates
Confidence Intervals to Determine Statistical Significance
Quick and easy way to interpret differences in rates or ratios
A 95 percent confidence interval would mean that if you were to repeat the analysis 100 times, you would expect the real value to be contained within the confidence interval 95 times.
Confidence Intervals to Determine Statistical Significance: RATIOS
ASK: Does the confidence interval include the number “1” ?
If “yes”, ratio not statistically significant (rates not statistically significant from each other)
How wide is the confidence interval?
Confidence intervals (CI) often used to interpret a ratio comparing two groups. For EXAMPLE, if the infant mortality rate is 20.0 per 1,000 in county A and 10.0 per 1,000 in County B, the ratio = 2. How would you interpret the ratio of 2 if the 95% CI around the ratio was 0.8 – 2.6 ?
Standard Error for Determining Statistically Significant Differences Between Two Rates
Used to directly compare two rates
Significant (at 95% confidence level) if Difference exceeds 1.96 standard
errors The probability that the observed
difference was due to random variation is less that 5% (0.05)
p1q1 p2q2
n1 n2√p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births
EXAMPLE: Interpreting Differences Between Two Rates
In 1991-1993, there were 3,132 infant deaths (d1) out of 307,567 live births (n1) and in 2001-2003 there were 2,892 infant deaths (d2) out of 353,711 live births (n2).
HINTS
First Step: Calculate p1 and p2: p1 = d1/ n1
p2 = d2/ n2
p1q1 p2q2
n1 n2√
p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births
Second Step: Apply SE formula
EXAMPLE: Interpreting Differences Between Two Rates
First Step:
Calculate p1 & p2: p1 = 3,132 / 307,567
p2 = 2,892 / 353,7110.01018 x 0.98982 0.01018 x
0.99182
307567 353711√p1 = infant mortality rate in 1991-1993 p2 = infant mortality rate in 2001-2003 qn = 1-p1 q2=1-p2 n = number of live births
Second Step: Apply SE formula
= 0.000236
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