The Perinatal Periods
of Risk Approach
Sanil Thomas
MS Biostatistics candidate
April 27, 2010
Introduction
• Infant mortality rate (IMR) is a critical indicator of nation’s
health
• IMR remains higher in United States than in other
industrialized countries
• But IMR does not provide sufficient information to
understand the factors that contribute to infant mortality
Introduction
• Traditional methods don’t include the fetal death counts
for the analysis of mortality rates
•
Fetal-infant mortality is a multi dimensional issue and a
detailed analytical approach to fetal- infant mortality is
needed to focus community initiatives for improving
maternal and infant health.
Objectives
• To look at Feto-Infant mortality in a new way
• Apply PPOR framework for New York State
• To see the distribution of common risk factors by county
level
Perinatal Periods of Risk (PPOR) Approach
• The Perinatal Periods of Risk Approach was developed
by Dr. Brian McCarthy from the W.H.O. Perinatal
Collaborative Center at CDC and other W.H.O.
colleagues.
• Simple method that is based on a strong conceptual
prevention
• The PPOR Data allow you to look at feto-infant mortality
in new ways
PPOR : 6 Basic Steps
Step 1: Assure Analytic and Community Readiness
Step 2: Conduct Analytic Phases of PPOR
Step 3: Develop Strategic Actions for Targeted
Prevention
Step 4: Strengthen Existing and/or Launch New
Prevention Initiatives
Step 5: Monitor and Evaluate Approach
Step 6: Sustain Stakeholder Investment and Political
Will
Analytic Phases of PPOR
Phase 1: Identifies populations and periods of risk with
the largest excess mortality.
Phase 2: Explains why the excess deaths occurred.
PPOR Examines Deaths in TWO
dimensions simultaneously:
• Age at death
• Weight at birth
The First Dimension Of PPOR Analysis:
Age at Death
Fetal
4 wks
Infancy
20 wks 28 wks
Spontaneous
Abortion
Early Late
Fetal Fetal
Postneonatal
Infant
Feto-Infant
Second Dimension: Birthweight
Birthweight
• Very Low Birthweight (PPOR limit)
= less than 1500 grams (3.3 pounds)
• Low Birthweight
= less than 2500 grams (5.5 pounds)
• Normal Birthweight
e.g., a 7.5-pound baby weighs 3,400 grams
PPOR “Map” fetal & infant deaths
Age at Death
Birthweight
500-1499 g 1
2
3
4
5
6
1500+ g
PPOR “Map” fetal & infant deaths
Age at Death
Birthweight
Fetal
Death
500-1499 g
1500+ g
Neonatal
Postneonatal
Maternal Health/
Prematurity
Maternal Newborn
Care
Care
Infant
Health
PPOR is about ACTION
(each period of risk is associated with a set of possible areas for action)
Maternal
Health/
Prematurity
Preconception Health
Health Behaviors
Perinatal Care
Maternal
Care
Prenatal Care High
Risk Referral
Obstetric Care
Newborn
Care
Perinatal Management
Neonatal Care
Pediatric Surgery
Infant
Health
Sleep Position
Breast Feeding
Injury Prevention
PPOR: Phase 2
• Poisson log linear modeling
• Covariates/Fixed effects
a. Mother’s race
b. Mother’s education
c. Mother’s age
d. Payor
• Random effect - County
PPOR: Phase 2
• Fetal death was not used
• 2004-2007
• Predicted death counts were used to obtain
smoothed death rates
• Modeling done for each county
 Relative risk calculated from the beta estimates
Data
• New York State Dept. of Health.
a. Electronic records of births
b. Linked birth-death cohort
c. selected fetal deaths
 Phase 1 : 2003-2007
 Phase 2 : 2004-2007
Software used
• SAS
• Excel
• ArcGIS
Results
Phase 1 Results
Death rates per 1000 live births and Fetal deaths
Obs
County
Total number of
deaths
Sum of Live
births and Fetal
deaths
(PPOR categories)
Total Death
Maternal
health/prematuri
ty
Maternal care
Newborn care
Infant health
1
ST LAWRENCE
61
6215
9.81
2.74
2.25
2.74
2.09
2
BROOME
101
10438
9.68
3.35
2.59
1.92
1.82
3
OSWEGO
62
6884
9.01
2.91
3.63
1.45
1.02
4
BRONX
1015
112785
9.00
4.34
2.66
0.79
1.21
5
JEFFERSON
76
8523
8.92
3.40
3.17
1.29
1.06
6
SCHENECTADY
76
9142
8.31
3.17
2.30
1.31
1.53
7
KINGS
1607
201738
7.97
3.66
2.35
0.86
1.10
8
ONEIDA
101
12905
7.83
2.40
1.55
1.63
2.25
9
ULSTER
72
9212
7.82
2.93
1.85
1.41
1.63
10
ALBANY
120
15904
7.55
3.58
1.76
0.75
1.45
11
RENSSELAER
66
8822
7.48
2.83
1.70
1.13
1.81
12
ERIE
373
50694
7.36
2.88
2.05
1.12
1.30
13
ONONDAGA
197
27648
7.13
2.89
1.77
1.23
1.23
14
QUEENS
990
153600
6.45
2.85
1.93
0.69
0.97
15
MONROE
273
43613
6.26
2.64
1.44
0.87
1.31
16
NEW YORK
629
102684
6.13
2.69
2.01
0.56
0.87
17
NIAGARA
70
11444
6.12
2.97
0.96
0.87
1.31
18
ORANGE
159
26316
6.04
2.24
1.25
1.18
1.37
19
RICHMOND
171
29176
5.86
3.29
1.34
0.55
0.69
20
ROCKLAND
134
23110
5.80
2.08
1.51
1.51
0.69
21
WESTCHESTER
342
61189
5.59
2.27
1.31
1.14
0.87
22
SUFFOLK
531
96216
5.52
2.53
1.29
0.91
0.79
23
NASSAU
411
77325
5.32
2.16
1.33
0.69
1.14
24
SARATOGA
60
11946
5.02
2.18
1.26
0.75
0.84
25
DUTCHESS
71
15763
4.50
2.03
0.38
1.33
0.76
Phase 1 Results
New York State
Death Rates per 1000 live births and fetal deaths
2.58
Maternal Health/ Prematurity
1.63
Maternal
Care
1.12
Newborn
Care
1.21
Infant
Health
Phase 2 Results
Poisson Log Linear model estimates
Solutions for Fixed Effects
mom_educn
mom_age
payor
Estimate
Standard
Error
DF
t Value
Pr > |t|
-5.7132
0.06320
56
-90.40
<.0001
-0.1806
0.1431
2730
-1.26
0.2071
Effect
Intercept
mom_race
mom_race
asian
mom_race
black_alone
0.9248
0.05255
2730
17.60
<.0001
mom_race
other_races
0.1056
0.07598
2730
1.39
0.1646
mom_race
z_white_alone
0
.
.
.
.
mom_educn
HighSchoolorAssoc
0.4346
0.05602
2730
7.76
<.0001
mom_educn
lessthan_HighSchool
0.6420
0.07174
2730
8.95
<.0001
mom_educn
z_Bachelors&above
0
.
.
.
.
mom_age
35&above
0.1367
0.05468
2730
2.50
0.0125
mom_age
lessthan20
0.2512
0.06412
2730
3.92
<.0001
mom_age
z_20to34
0
.
.
.
.
0.03220
0.04705
2730
0.68
0.4937
0
.
.
.
.
payor
medicaid
payor
other
Conclusions
• Infant mortality
 Higher risk ratio for black mothers relative to white mothers
 Higher risk ratio for mothers having education less than high school when
compared to mothers having education more than bachelors
 Higher risk ratio for mothers of age less than 20 when compared to mothers
of age between 20 and 34
• Smoothed rates are higher in St.Lawrence, Erie,
Schenectady, Oneida, Broome, Cortland etc
• Risk ratio for black mothers relative to white mothers are
higher in the counties Orleans, Oswego, Chenango and
Cortland
Limitation
• Missing data
 12428 records out of 497787 records
 246 deaths
• Inconsistent fetal data
Future study
• Detailed Phase 2 analysis including fetal deaths
• MHP and IH categories – Protocol for Phase 2
studies
• Cluster Analysis
• Spatial smoothing analysis
Reference
• http://www.citymatch.org/ppor_index.php
• Cai, J, Hoff GL, Dew PC et al. Perinatal periods of risk:
analysis of fetalinfant mortality rates in Kansas City, Missouri.
Matern Child Health J.2005;9:199-205
• Cai J, Hoff GL, Archer R et al. Perinatal periods of risk
analysis of infant mortality in Jackson County, Missouri. J
Public Health Manage Pract. 2007;13:270-277.
Acknowledgments
• Dr. Glen D. Johnson, PhD, MS, MA
• Dr. Marilyn A. Kacica, M.D.,M.P.H
Questions???