BALTIMORE COUNTY 1 - phpa.health.maryland.gov MIH Prof… · 21/11/2018 · 6 by Pre-Pregnancy...

Last updated: 11/21/2018

PPOR Notes: Minimum 60 fetal-infant deaths. Reference group: White NH mothers ages 20-34 with 13+ years of education in Maryland.

BALTIMORE COUNTY 1

____________________________________________________________________________________MATERNAL AND INFANT HEALTH PROFILE

BackgroundThe Office of Maternal and Child Health (MCH) Epidemiology in the MCH Bureau(MCHB) at the Maryland Department of Health created these health profiles to examinelocal maternal and infant health outcomes and risk factors compared to state averages. Localhealth departments should use these data and maps to identify and target population specificinterventions to reduce maternal health risks that contribute to increased fetal-infantmortality rates among minorities in Maryland.

While the statewide infant mortality rate (IMR) has decreased 32% since 1990, racial IMRdisparities persist. Infant mortality rates among Black non-Hispanic (NH) births areconsistently more than double the rates among White NH births. To eliminate this disparity,the IMR among Black NH births would have to decreased by approximately 60%. Theleading cause of infant deaths in Maryland are preterm birth/low birth weight and SuddenInfant Death Syndrome (SIDS) for both Black NH and White NH infants. Congenitalanomalies were the leading cause of death for Hispanic infants.

Perinatal periods of risk (PPOR) analysis is a method of examining all fetal and infant deathdata to identify opportunities to reduce perinatal mortality (Sappenfield, 2010). Results fromPhase 1 PPOR analysis suggests that half (49%) of excess, or preventable, fetal-infantmortality rates in Maryland during 2010-2017 was due to factors related to the maternalhealth and prematurity (MHP) period among Black NH births. Phase 2 analyses revealedthat the largest reductions in infant mortality and adverse pregnancy outcomes could beproduced by improving the social and economic environment of women which predisposesthem to poorer health and birth outcomes. Specifically, factors contributing most to racialdisparities in adverse pregnancy outcomes (APO: fetal or neonatal death, or very PTB andvery LBW births) include differences in marital status, education, insurance coverage,community socioeconomic disadvantage, hypertension, prior preterm birth or otherpregnancy outcomes, pre-pregnancy body mass index (BMI), and participation in theWomen, Infants and Children (WIC) program. Lack of prenatal care and tobacco use arealso associated with increased risks of APO, however, these factors do not appear to explainthe differences in APO rates between Black NH and White NH births in Maryland. Findingssuggest that eliminating the prevalence of hypertension could reduce APO’s by nearly 12%statewide. Drastic racial differences in marital status highlight the greater need for socialsupport and/or services for minority women to improve pregnancy outcomes (Salihu, 2014).For greater detail about preconception and prenatal risk factors, please visit the MarylandPRAMS website (PRAMS).

Programs should use these findings to develop evidence-based initiatives to improve the preconception and maternal health of women, and particularly Black NH women, to produce the greatest reductions in fetal and infant mortality in Maryland. For questions or comments, please contact the Maternal and Child Health Bureau at [email protected] or (410) 767-6713.

2017 Jurisdiction Ranks

Indicator Rank*Fetal-Infant Mortality Rate(FIMR)

12th

Preterm Birth (PTB, <37weeks)

20th

Low Birth Weight (LBW,<2500 grams)

17th

Very PTB & Very LBW 14th

Unmarried, no father listed 13th

Maternal Education: HighSchool Diploma or Less

10th

Maternal Hypertension(Chronic or Gestational)

13th

Medicaid Coverage 11th

Maternal Obesity 10th

Prior Preterm Birth 17th

Maternal Age Under 20Years Old

9th

Third Trimester or NoPrenatal Care Initiation

17th

Preconception or PrenatalSmoking

5th

Maternal Opioid UseDisorder

9th

Maternal Substance UseDisorder

10th

WIC Participation 12th

*Ranks are relative to the other 24 jurisdictions. Lower isbetter. N/a: rank not available due to insufficient data.

Perinatal Period of Risk (PPOR): Excess, or preventable, fetal-infant mortality rates bypopulation group, Baltimore County, 2010-2017

Population Group

0.6 0.41.0

1.6

HealthInfant

0.1 0.1 0.4 0.3

CareInfant

0.80.4

1.30.7

CareMaternal

3.5

0.9

8.3

4.0

PrematurityHealth/

Maternal

AllW

hite NH

Black NH

Hispanic

Medicaid

AllW

hite NH

Black NH

Hispanic

Medicaid

AllW

hite NH

Black NH

Hispanic

Medicaid

AllW

hite NH

Black NH

Hispanic

Medicaid

0

2

4

6

8

10

Dea

ths

per

1,00

0 pr

egna

ncie

s

22

13.6 14.1 14.1 14.4 13.8 13.4 13.0 13.113.7 12.8 13.1 12.2 13.2 12.9 13.9 14.0

0.02.55.07.5

10.012.515.0

preg

nanc

ies

Rat

e pe

r 1,

000

2010 2011 2012 2013 2014 2015 2016 2017

MarylandBaltimore County

Baltimore CountyMaryland

BALTIMORE COUNTYFetal-Infant Mortality RatesFetal-infant mortality rates (FIMR) represent the number of fetal (older than 20 weeks gestation) or infant deaths(younger than 365 days old) per 1,000 pregnancies in that year. NOTE: Source is linked infant birth and deathcertificate records which exclude records not linked due to certificate errors or migration and results in lowerFIMRs than those in Maryland VSA reports.

Of the 9,907 pregnancies in Baltimore County in 2017 there were 14 fetal or infant deaths for every 1,000pregnancies.

by Year

*Rates based on less than 5 events are suppressed. NH: non-Hispanic. Other NH includes American Indian andAsian or Pacific Islander.

Source: Maryland Vital Statistics Administration Linked Infant Birth-Death Certificate File

by Maternal Race and Year

10.7 11.7

11.2 9.0

Other NH

11.1 10.3

9.7 10.7

Hispanic

22.9 20.9

20.7 21.8

Black NH

9.1 9.1

9.0 9.4

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

33

by Maternal Age and Year

Fetal-Infant Mortality RatesBALTIMORE COUNTY

16.5 15.3

16.0 15.7

35+

11.8 12.0

11.1 12.4

25-34

15.9 14.2

14.7 14.7

20-24

20.4 19.2

17.4 16.1

<20

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore



by Maternal Age and Race, 2010-2017

10.4 26.6 14.6 11.8

9.6 26.7 23.9 9.9

35+ years

7.8 20.3 9.4 10.7

8.4 20.2 6.6 9.7

25-34 years

12.1 21.9 10.5 13.3

11.6 20.0 9.7 13.0

<25 years

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

44

by Insurance Coverage and Year


16.4 16.0

17.2 19.8

Other

16.6 15.2

13.1 15.6

Medicaid

11.8 11.1

12.2 11.4

Private

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

*Rates based on less than 5 events are suppressed. Other insurance includes self-pay and unknown. NH: non-Hispanic. Other NH includes American Indian and Asian or Pacific Islander.


by Insurance Coverage and Race, 2010-2017

10.1 25.0 13.1 19.8

9.7 34.0 10.5 25.0

Other

12.2 21.2 9.2 12.7

12.3 18.6 9.1 9.9

Medicaid

7.9 21.4 10.6 9.0

8.2 21.7 11.9 8.5

Private

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

10

20

30

40

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

55

by Maternal Educational Attainment and Year


10.5 10.0

9.5 10.0

College

16.8 16.5

14.1 16.7

High School Diploma

16.9 14.8

16.2 16.1

<High School

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore



by Maternal Educational Attainment and Race, 2010-2017

6.9 17.4 8.0 8.1

6.2 17.2 7.9 7.0

College

12.3 22.0 11.3 14.8

10.7 20.5 13.8 15.6

High School Diploma

16.6 26.1 10.2 14.5

20.2 25.9 8.8 10.9

<High School

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

66

by Pre-Pregnancy Body Mass Index (BMI) and Year


17.5 17.1

16.1 17.4

Obese

13.5 12.0

13.9 13.6

Overweight

10.2 9.6

8.1 9.9

Normal

11.0 10.8

8.3 9.8

Underweight

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore



by Pre-Pregnancy Body Mass Index (BMI) and Race, 2010-2017

10.9 24.3 11.6 15.8

11.3 23.2 12.9 11.8

Obese

8.9 19.1 9.8 10.5

10.3 20.3 10.6 9.6

Overweight

7.3 17.3 8.5 7.7

6.5 15.5 9.1 8.5

Normal

9.9 15.4 5.9 8.7

5.3 17.1 0.0 11.4

Underweight

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

77

by Marital Status and Year


22.4 19.1

21.0 21.3

Unmarried, No FL

16.6 9.5

15.1 9.5

Unmarried, FL

10.2 5.9

9.7 5.6

Married

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore

FL: father listed on the birth certificate



by Marital Status and Race, 2010-2017

16.2 23.7 15.0 21.8

16.0 26.3 8.4 *

Unmarried, No FL

9.9 17.9 7.7 12.0

9.0 15.7 8.2 16.7

Unmarried, FL

5.9 14.6 6.8 7.6

5.9 13.9 5.5 6.7

Married

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

25

30

Rat

e pe

r 1,

000

preg

nanc

ies

Maryland

CountyBaltimore


BALTIMORE COUNTY 8

Fetal-Infant Mortality Rates by Maternal Residence CensusTract, 2010-2017

Rate per 1,000 pregnancies

Suppressed (<5 events) No events 8.3 - 11.7

11.8 - 15.2 15.3 - 18.3 18.4 - 22.3

22.4 - 58.8

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

99

10.4 10.2 10.2 9.8 10.1 10.0 10.1 10.510.4 10.6 10.8 9.9 10.4 10.4 10.9 11.5

0

2

4

6

8

10

12

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYPreterm Birth (PTB, <37 weeks)Preterm birth describes infants born prior to 37 weeks gestation and is a leading cause of LBW and VLBW, andinfant death. Preterm-related causes of death accounted for 35% of all infant deaths in the U.S. in 2010, morethan any other single cause.

Of the 9,829 live births in Baltimore County in 2017, 11.5% were born preterm (<37 weeks gestation).

by Year


Source: Maryland Vital Statistics Administration


9.1 8.7

9.2 8.5

Other NH

8.8 9.3

8.8 10.8

Hispanic

12.7 12.8

12.9 13.8

Black NH

8.9 8.8

9.3 9.3

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1010


Preterm Birth (PTB, <37 weeks)BALTIMORE COUNTY

12.4 12.1

12.4 12.9

35+

9.5 9.5

9.8 10.2

25-34

9.9 9.8

10.3 10.5

20-24

10.3 11.0

10.9 11.4

<20

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




10.6 15.6 11.2 11.2

10.4 16.9 12.7 11.9

35+ years

8.3 12.3 8.6 8.0

8.9 13.1 9.2 7.9

25-34 years

8.7 11.9 8.4 8.0

9.7 11.8 9.7 8.0

<25 years

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1111



10.7 10.3

10.2 10.6

Other

11.3 11.3

11.8 12.2

Medicaid

9.3 9.3

9.8 10.0

Private

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




9.4 13.2 8.9 9.6

10.4 12.6 8.8 10.0

Other

10.2 13.2 9.2 8.3

11.1 13.6 11.1 8.3

Medicaid

8.3 12.0 8.9 9.0

8.7 13.2 9.3 9.0

Private

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1212



9.6 9.6

9.9 10.2

College

11.1 11.4

11.4 12.1

High School Diploma

10.8 10.9

11.4 12.0

<High School

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




8.4 12.0 9.1 8.9

8.7 12.9 9.9 8.6

College

9.9 13.4 9.1 8.8

10.6 13.5 10.7 9.8

High School Diploma

11.0 14.5 9.0 9.2

12.4 16.2 9.3 8.6

<High School

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1313



11.8 12.1

12.2 13.1

Obese

10.0 9.9

10.8 10.2

Overweight

9.0 9.0

9.0 9.7

Normal

10.9 10.5

11.8 8.5

Underweight

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




10.4 14.0 9.9 11.2

10.8 14.8 10.9 11.7

Obese

8.8 11.9 8.9 10.3

8.9 13.2 9.5 9.5

Overweight

8.1 11.7 8.4 8.1

8.7 11.5 9.5 8.1

Normal

9.9 15.0 8.6 7.0

9.9 14.4 4.6 6.9

Underweight

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1414



13.7 14.1

14.1 15.9

Unmarried, No FL

10.6 10.9

10.9 11.8

Unmarried, FL

9.2 9.1

9.6 9.6

Married

20132010-

20172014-

20132010-

20172014-

20132010-

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0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore





13.3 14.9 10.9 10.3

14.3 15.9 12.6 8.1

Unmarried, No FL

9.5 12.6 8.8 10.0

9.7 13.2 9.4 12.0

Unmarried, FL

8.3 11.7 8.9 8.8

8.8 12.5 9.9 8.6

Married

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 15

Preterm Birth (PTB, <37 weeks) by Maternal Residence CensusTract, 2010-2017

% of live births


8.2 - 9.5 9.6 - 10.9 11.0 - 12.3

12.4 - 18.6

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

1616

8.8 8.9 8.8 8.5 8.6 8.6 8.6 8.98.4 9.1 9.0 8.5 8.8 9.0 8.8 9.5

0

2

4

6

8

10

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYLow Birth Weight (LBW, <2500 grams)Low birth weight describes infants weighing less than 2500 grams, or 5.5 pounds, at birth and is a leading causeof neonatal mortality. Since low birth weight is typically associated with a preterm birth, many public healthinterventions focus on ways to reduce the rates of low birth weight, very low birth weight, and preterm birth asstrategies to reduce infant mortality.

Of the 9,829 live births in Baltimore County in 2017, 9.5% were low birth weight (<2500 grams).

by Year




8.5 8.3

9.0 7.8

Other NH

7.0 7.2

6.6 8.0

Hispanic

12.3 12.3

12.1 12.6

Black NH

6.8 6.6

7.0 7.1

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1717


Low Birth Weight (LBW, <2500 grams)BALTIMORE COUNTY

10.1 9.7

9.9 10.2

35+

7.9 7.9

8.0 8.3

25-34

9.3 9.4

9.2 10.0

20-24

10.9 10.9

11.2 11.1

<20

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

% o

f liv

e bi

rths

Maryland

CountyBaltimore




7.9 13.9 8.2 9.7

7.8 14.5 8.8 9.6

35+ years

6.2 11.5 6.6 7.8

6.6 11.7 6.7 7.8

25-34 years

7.1 12.7 7.3 9.2

7.9 12.4 7.8 9.2

<25 years

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1818



9.0 8.7

8.1 8.8

Other

10.5 10.3

10.4 10.6

Medicaid

7.7 7.5

8.0 8.1

Private

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

% o

f liv

e bi

rths

Maryland

CountyBaltimore




7.1 12.6 6.9 8.6

8.1 11.5 5.9 9.8

Other

8.8 13.0 7.3 8.3

9.1 12.7 8.7 8.0

Medicaid

6.0 11.3 6.9 8.4

6.3 12.2 7.1 8.5

Private

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

1919



8.0 7.9

8.2 8.3

College

10.0 10.5

9.7 10.8

High School Diploma

9.8 9.7

9.9 10.2

<High School

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

% o

f liv

e bi

rths

Maryland

CountyBaltimore




6.1 11.3 7.1 8.4

6.3 11.7 7.7 8.4

College

8.2 13.0 7.4 8.9

8.2 12.8 8.6 9.6

High School Diploma

10.0 15.0 6.9 8.0

11.7 16.1 6.4 6.2

<High School

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2020



9.4 9.5

9.6 10.1

Obese

8.2 8.2

8.5 8.2

Overweight

8.2 8.2

8.1 8.5

Normal

12.0 11.6

12.5 11.0

Underweight

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




7.0 12.3 6.9 8.9

7.6 12.5 7.2 9.4

Obese

6.2 11.2 6.6 9.0

6.4 11.4 6.6 8.3

Overweight

6.5 12.5 7.2 8.0

6.8 12.3 7.7 7.9

Normal

9.9 17.4 8.8 9.0

10.0 18.1 5.9 10.1

Underweight

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2121



13.4 13.6

12.8 14.6

Unmarried, No FL

9.7 10.0

9.8 10.4

Unmarried, FL

7.4 7.2

7.6 7.6

Married

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore





12.6 15.0 8.7 9.4

13.3 14.7 9.8 7.5

Unmarried, No FL

7.9 12.5 7.1 8.7

8.0 12.7 6.8 10.2

Unmarried, FL

5.9 10.5 6.7 8.4

6.2 11.1 7.4 8.3

Married

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 22

Low Birth Weight (LBW, <2500 grams) by Maternal ResidenceCensus Tract, 2010-2017

% of live births


6.6 - 7.7 7.8 - 8.9 9.0 - 10.4

10.5 - 15.8

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

2323

1.5 1.6 1.5 1.4 1.4 1.4 1.5 1.51.5 1.6 1.5 1.6 1.4 1.4 1.6 1.7

0.0

0.5

1.0

1.5

2.0

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYVery LBW (<1500 grams) & Very PTB (<32 weeks)Approximately 1 in 4 infants born very PTB & very LBW die before their first birthday. Very PTB & very LBWinfants also have an increased risk of developmental delays.

Of the 9,829 live births in Baltimore County in 2017, 1.7% were born very premature.

by Year




1.1 1.0

1.4 1.0

Other NH

1.1 1.1

1.1 1.3

Hispanic

2.7 2.6

2.7 2.7

Black NH

0.9 0.9

0.9 0.9

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

0.5

1.0

1.5

2.0

2.5

3.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2424


Very LBW (<1500 grams) & Very PTB (<32 weeks)BALTIMORE COUNTY

1.9 1.8

2.0 1.8

35+

1.3 1.3

1.4 1.4

25-34

1.6 1.5

1.4 1.9

20-24

2.0 1.8

1.9 1.6

<20

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

0.5

1.0

1.5

2.0

2.5

3.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




1.1 3.2 1.5 1.3

1.1 3.4 2.0 1.3

35+ years

0.8 2.5 1.1 0.9

0.8 2.7 1.1 1.0

25-34 years

1.0 2.5 0.9 1.0

1.2 2.3 1.1 1.6

<25 years

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

1

2

3

4

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2525



1.8 1.6

1.7 1.7

Other

2.0 1.7

1.9 1.7

Medicaid

1.2 1.3

1.3 1.4

Private

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

0.5

1.0

1.5

2.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




1.1 3.1 1.0 1.1

1.0 3.3 1.0 1.5

Other

1.1 2.6 1.2 1.1

1.1 2.5 1.5 1.4

Medicaid

0.8 2.4 1.1 1.0

0.8 2.8 1.1 1.0

Private

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

1

2

3

4

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2626



1.3 1.3

1.5 1.3

College

1.8 1.8

1.5 1.9

High School Diploma

1.6 1.6

1.7 1.8

<High School

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

0.5

1.0

1.5

2.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




0.8 2.4 1.1 1.0

0.8 2.6 1.2 1.0

College

1.1 2.7 1.2 1.0

1.0 2.5 1.7 1.3

High School Diploma

1.2 2.9 1.0 1.2

1.4 3.7 1.0 1.3

<High School

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

1

2

3

4

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2727



2.0 2.0

1.9 2.1

Obese

1.4 1.4

1.7 1.3

Overweight

1.1 1.1

1.1 1.2

Normal

1.3 1.4

1.4 1.2

Underweight

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

0.5

1.0

1.5

2.0

2.5

3.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore




1.2 3.0 1.4 1.5

1.3 3.0 1.0 0.8

Obese

0.8 2.4 1.0 1.2

0.8 2.7 1.3 1.1

Overweight

0.7 2.1 0.9 0.9

0.8 2.1 1.4 1.1

Normal

1.0 2.4 0.7 0.7

1.0 1.9 0.0 1.6

Underweight

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0.0

0.5

1.0

1.5

2.0

2.5

3.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore

2828



2.9 2.7

3.0 3.1

Unmarried, No FL

1.7 1.7

1.6 1.7

Unmarried, FL

1.2 1.2

1.3 1.3

Married

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

1

2

3

4

% o

f liv

e bi

rths

Maryland

CountyBaltimore





1.9 3.4 1.7 2.4

2.1 3.8 1.5 3.1

Unmarried, No FL

0.9 2.5 1.1 1.2

0.8 2.5 0.9 1.1

Unmarried, FL

0.8 2.3 1.0 1.0

0.9 2.5 1.5 1.1

Married

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

NHWhite

NHBlack Hisp

NHOther

0

1

2

3

4

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 29

Very LBW (<1500 grams) & Very PTB (<32 weeks) by MaternalResidence Census Tract, 2010-2017

% of live births


1.4 - 1.6 1.7 - 1.9 2.0 - 2.6

2.7 - 5.4

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

3030

30.2 30.2 30.1 30.0 27.8 30.4 28.1 30.229.9 30.6 29.8 30.1 30.2 31.8 30.6 32.3

0

10

20

30

40

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Unmarried, No Father ListedBirths to unmarried women with no father listed on the birth certificate have an increased risk of adverse birthoutcomes. (Ngui, 2009; Luo, 2004; Alio, 2010). Mothers with a lack of paternal involvement are more likely toexperience greater psychosocial stress due to insufficient economic and social support which can lead to poorhealth behaviors and adverse birth outcomes.

Of the 9,829 live births in Baltimore County in 2017, 32.3% were to unmarried women with no father listedon the birth certif icate.

by Year

*Rates based on less than 5 events are suppressed. FL: father listed on the birth certificate. NH: non-Hispanic.Other NH includes American Indian and Asian or Pacific Islander.



7.1 7.1

6.7 8.4

Other NH

45.9 42.9

47.5 47.2

Hispanic

42.4 40.4

44.7 45.8

Black NH

20.2 19.7

22.6 22.6

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

10

20

30

40

50

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 31

Risk Factor: Unmarried, No Father Listed by MaternalResidence Census Tract, 2010-2017

% of live births


13.4 - 24.2 24.3 - 34.8 34.9 - 43.2

43.3 - 55.9

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

3232

36.9 35.5 35.0 34.1 33.0 33.4 33.0 32.833.0 31.9 30.4 30.8 30.0 30.3 29.8 30.0

0

10

20

30

40

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal Education: High School Diploma or LessLow educational attainment serves as a proxy for lower socioeconomic status and is associated with increasedadverse birth outcome risks.

Of the 9,829 live births in Baltimore County in 2017, 30% were to women with a high school education orless.

by Year




16.3 16.1

23.6 26.5

Other NH

69.9 67.1

71.4 66.3

Hispanic

41.9 37.8

34.8 32.0

Black NH

23.0 20.2

24.9 22.0

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

20

40

60

80

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 33

Risk Factor: Maternal Education: High School Diploma or Lessby Maternal Residence Census Tract, 2010-2017

% of live births


13.0 - 21.8 21.9 - 33.8 33.9 - 44.6

44.7 - 68.4

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

3434

6.5 6.6 6.9 7.7 8.2 9.2 9.2 10.27.1 7.7 7.0 8.0 8.9 9.1 10.3 11.0

0

2

4

6

8

10

12

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal Hypertension (Chronic or Gestational)Hypertension before and during pregnancy puts women at higher risk for preeclampsia, cesarean section, pretermbirth, and a low birth weight baby.

Of the 9,829 live births in Baltimore County in 2017, 11% were to women who had chronic or pregnancy-associated hypertension.

by Year




3.9 4.9

4.4 5.3

Other NH

4.8 6.7

4.9 7.6

Hispanic

9.0 12.3

10.4 13.5

Black NH

6.6 8.7

6.5 8.6

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 35

Risk Factor: Maternal Hypertension (Chronic or Gestational) byMaternal Residence Census Tract, 2010-2017

% of live births


5.6 - 7.5 7.6 - 9.0 9.1 - 10.9

11.0 - 17.2

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

3636

26.2 29.5 31.0 32.1 34.1 36.6 36.4 38.226.5 29.1 30.0 31.9 32.9 35.7 35.7 39.0

0

10

20

30

40

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Medicaid CoverageMedicaid paid births serve as a proxy for lower socioeconomic status and is associated with increased adversebirth outcome risks.

Of the 9,829 live births in Baltimore County in 2017, 39% were Medicaid paid births.

by Year




16.3 22.9

27.1 37.6

Other NH

36.7 53.0

35.2 45.6

Hispanic

43.8 50.6

42.2 49.1

Black NH

19.5 22.1

21.1 24.5

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

10

20

30

40

50

60

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 37

Risk Factor: Medicaid Coverage by Maternal Residence CensusTract, 2010-2017

% of live births


13.5 - 23.3 23.4 - 36.5 36.6 - 45.3

45.4 - 74.3

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

3838

22.3 22.4 23.3 23.2 23.8 24.8 25.0 25.823.5 23.5 24.6 24.2 24.7 25.5 26.1 27.2

0

5

10

15

20

25

30

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal ObesityObesity during pregnancy is associated with maternal risks such as gestational diabetes, preeclampsia, stillbirthand congenital anomalies (Leddy, 2008).

Of the 9,829 live births in Baltimore County in 2017, 27.2% were to obese women.

by Year

*Rates based on less than 5 events are suppressed. Obesity defined as a pre-pregnancy body mass index (BMI)score of 30 or greater. NH: non-Hispanic. Other NH includes American Indian and Asian or Pacific Islander.



8.8 10.7

10.8 13.0

Other NH

19.1 22.6

20.7 23.4

Hispanic

32.2 34.6

33.7 36.6

Black NH

19.5 21.1

20.7 21.7

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

10

20

30

40

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 39

Risk Factor: Maternal Obesity by Maternal Residence CensusTract, 2010-2017

% of live births


15.4 - 22.2 22.3 - 26.9 27.0 - 31.8

31.9 - 40.5

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

4040

2.6 2.7 2.9 3.3 3.7 4.0 3.6 4.12.6 3.2 3.1 4.0 4.1 4.1 3.9 4.7

0

1

2

3

4

5

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Prior Preterm BirthWomen with a prior preterm birth are more likely to have a repeat preterm birth (Adams, 2000). Repeat PTB'smay also serve as a marker for persistent physiological risks to maternal health and is associated with greaterrisks to infant survival.

Of the 9,829 live births in Baltimore County in 2017, 4.7% were to women with a prior preterm birth.

by Year




1.8 2.4

2.0 2.2

Other NH

2.2 3.5

2.6 4.2

Hispanic

3.8 5.3

4.2 5.7

Black NH

2.6 3.2

2.9 3.6

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

1

2

3

4

5

6

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 41

Risk Factor: Prior Preterm Birth by Maternal Residence CensusTract, 2010-2017

% of live births


2.6 - 3.3 3.4 - 4.0 4.1 - 5.2

5.3 - 9.0

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

4242

7.5 6.7 6.0 5.2 4.7 4.4 4.2 3.86.5 6.0 5.0 4.4 4.0 3.9 3.5 3.0

0

2

4

6

8

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal Age Under 20 Years OldTeen childbearing often limits the educational and economic opportunties for young women and is associatedwith a greater risk of adverse birth outcomes. (Ventura, 2014) Approximately, 8 in 10 births to women under 20years old are unintended. (MD PRAMS, 2018)

Of the 9,829 live births in Baltimore County in 2017, 3% were to women under 20 years old.

by Year




1.0 0.9

1.1 1.2

Other NH

8.1 7.1

7.1 6.6

Hispanic

10.1 6.1

8.6 4.9

Black NH

4.0 2.6

4.1 2.6

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 43

Risk Factor: Maternal Age Under 20 Years Old by MaternalResidence Census Tract, 2010-2017

% of live births


3.0 - 4.3 4.4 - 5.9 6.0 - 7.9

8.0 - 13.8

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

4444

7.7 8.5 8.8 9.4 9.2 9.0 8.6 7.57.0 7.2 7.9 9.3 9.1 9.0 8.7 7.2

0

2

4

6

8

10

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Third Trimester or No Prenatal Care InitiationBabies born to women who do not receive prenatal care are three times more likely to be born at a low birthweight and five times more likely to die than babies born to mothers receiving prenatal care.

Of the 9,829 live births in Baltimore County in 2017, 7.2% were to women who initiated prenatal care in thethird trimester or had no prenatal care.

by Year

*Rates based on less than 5 events are suppressed. Note: percentages are calculated excluding missing or unknownvalues of PNC initiation. NH: non-Hispanic. Other NH includes American Indian and Asian or Pacific Islander.



7.9 7.7

9.4 8.2

Other NH

11.6 11.2

12.5 12.6

Hispanic

12.3 12.0

9.9 11.6

Black NH

5.4 5.4

5.6 5.8

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 45

Risk Factor: Third Trimester or No Prenatal Care Initiation byMaternal Residence Census Tract, 2010-2017

% of live births


5.2 - 6.9 7.0 - 8.5 8.6 - 10.5

10.6 - 15.1

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

4646

12.8 12.8 12.6 12.8 11.2 10.4 9.5 8.813.9 13.2 12.2 12.1 12.0 10.9 9.7 9.5

0.0

2.5

5.0

7.5

10.0

12.5

15.0

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Preconception or Prenatal SmokingTobacco is the most commonly used substance during pregnancy and is associated with adverse birth outcomessuch as miscarriage, placental abruption, placental insufficiency, and low birth weight.

Of the 9,829 live births in Baltimore County in 2017, 9.5% were to women who reported smoking before orduring their pregnancy.

by Year




5.0 2.6

3.0 2.2

Other NH

4.0 2.8

4.1 3.9

Hispanic

10.9 9.4

7.5 6.9

Black NH

18.0 14.4

19.0 15.9

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

5

10

15

20

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 47

Risk Factor: Preconception or Prenatal Smoking by MaternalResidence Census Tract, 2010-2017

% of live births


5.6 - 8.1 8.2 - 11.6 11.7 - 21.1

21.2 - 36.6

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

4848

11.3 12.4 14.7 14.8 14.2 16.1 16.7 17.114.7 15.1 19.0 17.1 15.3 17.4 17.7 20.0

0

5

10

15

20

25

hosp

italiz

atio

nspe

r 1,

000

mat

erna

l

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal Opioid Use Disorder (OUD)Opioids include heroin, morphine, codeine, oxycodone, hydrocodone, etc. Maternal opioid use disorder has beenassociated with preterm labor, stillbirth, birth defects, neonatal abstinence syndrome, and maternal mortality(Patrick, 2015; Maeda, 2014). Nationally, the rate of opioid use disorder during delivery hospitalizationsincreased 67% from 2010-2014 (Haight, 2017).

Of the 10,146 maternal hospitalizations in Baltimore County in 2017, there were 20 with an OUD diagnosisfor every 1,000 maternal hospitalizations.

by Year


Source: Maryland Health Services Cost Review Commission (HSCRC) Inpatient Files for maternal (prenatal,delivery, or postpartum) hospitalizations. Please note, diagnosis coding transitioned from ICD-9 to ICD-10beginning October 2015. Note, OUD diagnoses based on AHRQ recommended ICD-9 and ICD-10 codes (Heslin,2017).


2.2 2.6

* *

Other NH

1.6 1.9

* 3.6

Hispanic

5.6 6.7

4.7 4.7

Black NH

24.6 30.7

28.9 32.8

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

10

20

30

40

per

1,00

0 m

ater

nal h

o...

Maryland

CountyBaltimore

Source: Maryland Health Services Cost Review Commission (HSCRC) Inpatient Files for maternal (prenatal, delivery, or postpartum) hospitalizations. Please note, diagnosiscoding transitioned from ICD-9 to ICD-10 beginning October 2015. Note, OUD diagnoses based on AHRQ recommended ICD-9 and ICD-10 codes (Heslin, 2017).

BALTIMORE COUNTY 49

Risk Factor: Maternal Opioid Use Disorder (OUD) by MaternalResidence Census Tract, 2013-2016

per 1,000 maternal hospitalizations


28.1 - 56.4 56.5 - 61.2 61.3 - 76.0

76.1 - 104.5

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

5050

27.1 27.3 30.4 30.6 30.8 33.8 36.3 40.927.0 25.9 30.7 30.3 27.5 28.5 34.3 40.9

01020304050

hosp

italiz

atio

nsm

ater

nal

per

1,00

0

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYRisk Factor: Maternal Substance Use Disorder (SUD)In addition to opioid, other substances can lead to adverse birth outcomes. Cocaine use during pregnancy canlead to spontaneous abortion, preterm births, placental abruption, and congenital anomalies. Alcohol use duringpregnancy can lead to spontaneous abortion, growth restriction, birth defects, and mental retardation (Keegan,2010). This indicator represents a SUD diagnosis during a maternal hospitalization for the following substances:Opioids, Cocaine, Cannabis, Alcohol, Sedatives, and Hallucinogens.

Of the 10,146 maternal hospitalizations in Baltimore County in 2017, there were 40.9 with an SUDdiagnosis for every 1,000 maternal hospitalizations.

by Year


Source: Maryland Health Services Cost Review Commission (HSCRC) Inpatient Files for maternal (prenatal,delivery, or postpartum) hospitalizations. Please note, diagnosis coding transitioned from ICD-9 to ICD-10beginning October 2015. Note, SUD diagnoses based on AHRQ recommended ICD-9 and ICD-10 codes (Fingar,2015; Heslin, 2017).


6.4 7.0

5.7 6.0

Other NH

4.3 6.6

* 9.0

Hispanic

32.7 42.2

22.2 29.7

Black NH

37.3 46.6

39.8 45.6

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

10

20

30

40

50

per

1,00

0 m

ater

nal h

o...

Maryland

CountyBaltimore

Source: Maryland Health Services Cost Review Commission (HSCRC) Inpatient Files for maternal (prenatal, delivery, or postpartum) hospitalizations. Please note, diagnosiscoding transitioned from ICD-9 to ICD-10 beginning October 2015. Note, SUD diagnoses based on AHRQ recommended ICD-9 and ICD-10 codes (Fingar, 2015; Heslin,2017).

BALTIMORE COUNTY 51

Risk Factor: Maternal Substance Use Disorder (SUD) byMaternal Residence Census Tract, 2013-2016

per 1,000 maternal hospitalizations


40.4 - 54.0 54.1 - 70.2 70.3 - 93.1

93.2 - 141.8

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

5252

40.9 41.1 40.8 39.7 38.6 38.2 36.8 35.537.7 38.5 37.7 38.1 36.6 36.5 35.6 35.6

0

10

20

30

40

50

% o

f liv

e bi

rths

2010 2011 2012 2013 2014 2015 2016 2017



BALTIMORE COUNTYCharacteristic: Women, Infants and Children (WIC) ProgramParticipationPrenatal WIC participation is associated with lower infant mortality rates. WIC prenatal care benefits reduce therate of LBW babies by 25% and VLBW babies by 44%. Women participating in WIC have been found to havelonger pregnancies and are more likely to receive adequate prenatal care.

Of the 9,829 live births in Baltimore County in 2017, 35.6% were to women who were enrolled in WIC.

by Year




20.0 19.7

26.9 31.8

Other NH

68.1 63.1

68.9 60.7

Hispanic

57.1 52.6

56.5 53.0

Black NH

23.7 19.8

24.0 20.5

White NH

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

20132010-

20172014-

0

20

40

60

80

% o

f liv

e bi

rths

Maryland

CountyBaltimore


BALTIMORE COUNTY 53

Characteristic: Women, Infants and Children (WIC) ProgramParticipation by Maternal Residence Census Tract, 2010-2017

% of live births


12.4 - 26.6 26.7 - 39.8 39.9 - 54.2

54.3 - 71.8

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Source: Maryland Vital Statistics Administration and Office of MCH Epidemiology. Risk represents weighted mean predicted probability of fetal deaths, neonatal deaths, orvery PTB and very LBW births (<1,500g & <32 weeks) adjusted for maternal, hospital, and community characteristics stratified by jurisdiction among singleton pregnancies.Lowest and Highest indicate areas whose estimated risk is in the lower 5th and upper 95th percentile of the jurisdiction grouping, respectively. Data based on fewer than 5pregnancies has been suppressed.

Baltimore County Adverse Pregnancy OutcomeRisks

54

All Races

No data Suppressed Lowest

Highest

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Black non-Hispanic


Highest

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

White non-Hispanic


Highest

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Hispanic


Highest

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Source: US Census American Community Survey 2016 Five-year Census Tract Estimates

Baltimore County Social Determinants of Health55

Adult Poverty Rates (ages 18-59)

% of adult residents

No data 0.0 0.2 - 3.1

3.2 - 5.1 5.2 - 9.1 9.2 - 12.9

13.0 - 82.5

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Median Household Income

Income in 2016 inflation-adjusted dollars ($)

No data 0.0 11,726 - 52,649

52,649 - 63,958 63,958 - 75,288 75,288 - 92,500

92,500 - 192,188

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

No Health Insurance Coverage

% of adult residents, ages 18-64

No data 0.0 0.6 - 4.3

4.4 - 6.1 6.2 - 8.6 8.7 - 12.0

12.1 - 26.2

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

Houses Built Before 1950

% of households

No data 0.0 0.7 - 4.5

4.6 - 9.6 9.7 - 19.0 19.1 - 31.9

32.0 - 79.7

Towson

Catonsville Dundalk

Cockeysville

Randallstown

Middle River

5656

REFERENCESr

Alio AP, Kornosky JL, Mbah AK, et al. (2010). The impact of paternal involvement on feto-infant morbidity among Whites, Blacks andHispanics. Maternal and Child Health Journal, 14(5), 735–741. doi:10.1007/s10995-009-0482-1.

Adams MM, Elam-Evans LD, Wilson HG, Gilbertz DA (2000). Rates of and factors associated with recurrence of preterm delivery. JAMA,283(12):1591-6. 10.1001/jama.283.12.1591.

Fingar KR, Stocks C, Weiss AJ, Owens PL (2015). Neonatal and Maternal Hospital Stays Related to Substance Use, 2006–2012. HCUPStatistical Brief #193. July 2015. Agency for Healthcare Research and Quality, Rockville, MD.http://www.hcup-us.ahrq.gov/reports/statbriefs/sb193-Neonatal-Maternal-Hospitalizations-SubstanceUse.pdf.

Haight SC, Ko JY, Tong VT, Bohm MK, Callaghan WM. Opioid Use Disorder Documented at Delivery Hospitalization - United States,1999–2014. MMWR Morb Mortal Wkly Rep 2018;67:845-849.

Heslin KC, Owens PL, Karaca Z, Barrett ML, Moore BJ, Elixhauser A (2017). Trends in Opioid-related Inpatient Stays Shifted After the USTransitioned to ICD-10-CM Diagnosis Coding in 2015. Medical Care, 55(11):918-923.

Keegan J, Parva M, Finnegan M, Gerson A, Belden M (2010). Addiction in pregnancy. Journal of Addictive Diseases, 29(2):175-191.

Leddy MA, Power ML, Schulkin J (2008). The impact of maternal obesity on maternal and fetal health. Reviews in Obstetrics & Gynecology,1:170-178.

Luo ZC, Wilkins R, Kramer MS (2004). Disparities in pregnancy outcomes according to marital and cohabitation status. Obstetrics andGynecology, 103(6), 1300–1307. doi:10.1097/01. AOG.0000128070.44805.1f.

Maeda A, Bateman BT, Clancy CR, Creanga AA, Leffert LR. Opioid abuse and dependence during pregnancy: temporal trends and obstetricaloutcomes. Anesthesiology 2014;121:1158–65. https://doi.org/10.1097/ALN.0000000000000472.

Maryland (MD) PRAMS Report, 2012-2015 Births. January 2018. Available at:https://phpa.health.maryland.gov/mch/Documents/2012-2015%20PRAMS%20report_rev.pdf

Ngui E, Cortright A, & Blair K (2009). An investigation of paternity status and other factors associated with racial and ethnic disparities inbirth outcomes in Milwaukee, Wisconsin. Maternal and Child Health Journal, 13(4), 467–478. doi:10.1007/s10995-008-0383-8.

Patrick SW, Davis MM, Lehmann CU, Cooper WO. Increasing incidence and geographic distribution of neonatal abstinence syndrome:United States 2009 to 2012. J Perinatol 2015;35:650–5. https://doi.org/10.1038/jp.2015.36.

Salihu HM, Salemi JL, Nash MC, et al. (2014). Assessing the Economic Impact of Paternal Involvement: A Comparison of the GeneralizedLinear Model Versus Decision Analysis Trees. Maternal Child Health Journal, 18:1380–1390.

Sappenfield WM, Peck MG, Gilbert CS, et al (2010). Perinatal Periods of Risk: Analytic Preparation and Phase 1 Analytic Methods forInvestigating Feto-Infant Mortality. Maternal and Child Health Journal, 14:838-850.

Sappenfield WM, Peck MG, Gilbert CS, et al (2010). Perinatal Periods of Risk: Phase 2 Analytic Methods for Further InvestigatingFeto-Infant Mortality. Maternal and Child Health Journal, 14:851-863.

Ventura SJ, Hamilton BE, Mathews TJ (2014). National and state patterns of teen births in the United States, 1940–2013. National vitalstatistics reports; vol 63 no 4. Hyattsville, MD: National Center for Health Statistics.

More information about maternal preconception and prenatal risk factors and trends are available in Maryland Pregnancy Risk AssessmentMonitoring System (PRAMS) Reports and Focus Briefs available here: https://phpa.health.maryland.gov/mch/Pages/prams_report.aspx

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