Analysis of Oral Health in Montana: Point-in-Time PRAMS Family and Community Health Bureau Data...

Analysis of Oral Health in Analysis of Oral Health in Montana:Montana:

Point-in-Time PRAMS Point-in-Time PRAMS

Family and Community Health BureauFamily and Community Health BureauData Monitoring SectionData Monitoring Section

Report Prepared By Rosina Everitte, MPHReport Prepared By Rosina Everitte, MPHMCH Epidemiological StatisticianMCH Epidemiological Statistician

[email protected]@mt.gov

Why PRAMS?Why PRAMS?

The PRAMS surveyThe PRAMS survey

is an invaluable toolis an invaluable tool

because..because..

it attempts to collect data not readilyit attempts to collect data not readily

accessible by other means including as Vitalaccessible by other means including as Vital

Statistics, Census Data, registries, Statistics, Census Data, registries,

or other structured data repositoriesor other structured data repositories

For Montana, it also serves as a baseline forFor Montana, it also serves as a baseline for

many projects and programs such as many projects and programs such as

Oral HealthOral Health

CDC PRAMSCDC PRAMS

Pregnancy Risk Assessment Monitoring Survey (PRAMS) 5-Pregnancy Risk Assessment Monitoring Survey (PRAMS) 5-year, ongoing surveillance studyyear, ongoing surveillance study

Originated from the CDC in 1987Originated from the CDC in 1987 Collects state-specific, population-based dataCollects state-specific, population-based data Approximately 1,300 to 3,400 unweighted live births collected via Approximately 1,300 to 3,400 unweighted live births collected via

birth certificates every yearbirth certificates every year State-optional over-sampling of minority populationsState-optional over-sampling of minority populations Standardized protocol for data collection, including mailings and Standardized protocol for data collection, including mailings and

telephone communicationtelephone communication Core and state-tailored questionnaireCore and state-tailored questionnaire Maternal information including behaviors and risk factors relative to Maternal information including behaviors and risk factors relative to

the pre-,intermediate, and post-pregnancy experiencethe pre-,intermediate, and post-pregnancy experience Minimum 70% response rateMinimum 70% response rate

Montana PRAMSMontana PRAMS

3-year, point-in-time cross-sectional surveillance study initiated in 3-year, point-in-time cross-sectional surveillance study initiated in 20022002

One-year sampling of live birth cohort via birth certificates from first One-year sampling of live birth cohort via birth certificates from first three months of 2002three months of 2002

Over-sampling of young mothers under 20 years of ageOver-sampling of young mothers under 20 years of age

1,363 unweighted responses, 10,720 weighted1,363 unweighted responses, 10,720 weighted

77% success rate77% success rate

12.34% response rate12.34% response rate

Other aspects of Montana PRAMS are not markedly different than Other aspects of Montana PRAMS are not markedly different than the basic CDC PRAMSthe basic CDC PRAMS

Oral Health:Oral Health:Why do we care?Why do we care?

Definitive oral health disparities in the MCH populationDefinitive oral health disparities in the MCH population

Bacteria affiliated with oral disease can be transmitted to babyBacteria affiliated with oral disease can be transmitted to baby

Oral health diseases are preventableOral health diseases are preventable

Oral health risk factors are prominent including:Oral health risk factors are prominent including:Low fluoridation rates in water systems ( ~ 24% in 2002)Low fluoridation rates in water systems ( ~ 24% in 2002)33rdrd highest smokeless tobacco rate highest smokeless tobacco rateAccess to oral health care is problematic across the stateAccess to oral health care is problematic across the state

Poor oral health may lead to negative birth outcomesPoor oral health may lead to negative birth outcomes

Briefing on Oral HealthBriefing on Oral HealthCommon oral diseases – Early Childhood Caries (ECC – i.e. baby bottle tooth Common oral diseases – Early Childhood Caries (ECC – i.e. baby bottle tooth decay), caries, periodontal disease, and oral cancerdecay), caries, periodontal disease, and oral cancer

Caries process involves fermentation of carbohydrates into acids, which Caries process involves fermentation of carbohydrates into acids, which demineralize the tooth enamel causing cariesdemineralize the tooth enamel causing caries

With optimal amounts of fluoride (@ 1 PPM), early caries can be prevented and With optimal amounts of fluoride (@ 1 PPM), early caries can be prevented and even reversed. Root caries in adults, due to gum recession, can also be preventedeven reversed. Root caries in adults, due to gum recession, can also be prevented

Approximately 76% of Montanans do not have access to optimal fluoridated water, Approximately 76% of Montanans do not have access to optimal fluoridated water, however, there are locations in Montana where natural fluoride levels are extremely however, there are locations in Montana where natural fluoride levels are extremely elevated, which may cause fluorosiselevated, which may cause fluorosis

Maternal transmission of Maternal transmission of Streptococcus Mutans – Streptococcus Mutans – a common bacteria found in the a common bacteria found in the mouth is passed on via the mother, with an infant having a typical window of mouth is passed on via the mother, with an infant having a typical window of infectivity for children less than 2 years of ageinfectivity for children less than 2 years of age

New evidence suggests caesarian infants may have an earlier window of infectivity at New evidence suggests caesarian infants may have an earlier window of infectivity at around 17 months, when compared to vaginally-delivered infants (29 months)around 17 months, when compared to vaginally-delivered infants (29 months)

Children’s health may be impacted by caries, i.e. growth retardation and failure to Children’s health may be impacted by caries, i.e. growth retardation and failure to thrive, inability to learn in school, spread of disease to other areas of the body thrive, inability to learn in school, spread of disease to other areas of the body

Adult health are affected as well, especially with regard to periodontal disease, i.e. Adult health are affected as well, especially with regard to periodontal disease, i.e. new associations with stroke and cardiovascular disease and negative birth new associations with stroke and cardiovascular disease and negative birth outcomes to name a fewoutcomes to name a few

Legend

Average >= 1.21 PPM

0.71 – 1.20 PPM (Optimal)

0.41 – 0.70 PPM

0.00 – 0.40 PPM

µ Averaged fluoride per county

Montana Public Water Systems Average Fluoridation Levels By County

Data originally from DEQ - November 8, 2005

♀ Map created by Rosina Everitte, MCH Epidemiological Statistician

ValleyPhillips

Fergus Garfield

Big Horn

Custer

Rosebud

Carter

McCone

Dawson

Carbon

Prairie

Fallon

Richland

Roosevelt

Yellowstone

Stillwater

Daniels Sheridan

Petroleum

Musselshell

Judith Basin

Sweet Grass

Wheatland

Wibaux

TreasureGolden Valley

Powder River

Madison

Ravalli

Powell

Lake

Missoula

Granite

Mineral

Sanders

Flathead

Silver Bow

Hill

Blaine

Park

Glacier

ChouteauTeton

Toole

Cascade

Meagher

Lewis & Clark

Liberty

Pondera

Broadwater

Jefferson

Beaverhead

Deer Lodge

Lincoln

Gallatin

µ=1.09 µ=0.40

µ=0.63

µ=0.63

µ=0.34

µ=0.67

µ=0.66

µ=0.67µ=0.21

µ=0.22

µ= 0.09

µ=1.45

µ=0.37

µ=0.38µ=0.66

µ=0.38 µ=0.89

µ=0.60

µ=1.14

µ=0.24

µ=0.25

µ=1.07

µ=1.75

µ=0.80

µ=2.20µ=0.90

µ=0.13

µ=0.36

µ=0.29

µ=0.62µ=0.18

µ=0.22

µ=0.81

µ=0.33

µ= 0.55

µ=0.15

µ=4.42

µ=0.17µ=2.48

µ=0.47

µ=0.49

µ=0.51

µ=2.31

µ=0.20

µ=0.46

µ=1.25

µ=0.27

µ=0.45

µ=0.48µ=0.84

µ=0.74

µ=0.37µ=1.24

µ= 2.06

µ=0.79

µ= 0.24

Montana Public Water Systems Proportional Fluoridation Level Inadequacy By County


Legend

75.01 to 100.0% Inadequacy




µ Averaged fluoride per county

Montana Public Water Systems Proportional Fluoridation Level Inadequacy By County

Overall Inadequacy = 83.76%*a

* Inadequacy criteria = less than 0.7 parts per million a DEQ data pulled on November 8, 2005


µ= 2.06

ValleyPhillips

Fergus Garfield

Big Horn

Custer

Rosebud

Carter

McCone

Dawson

Carbon

Prairie

Fallon

Richland

Roosevelt

Yellowstone

Stillwater

Daniels Sheridan

Petroleum

Musselshell

Judith Basin

Sweet Grass

Wheatland

Wibaux


Powder River

Madison

Ravalli

Powell

Lake

Missoula

Granite

Mineral

Sanders

Flathead

Silver Bow

Hill

Blaine

Park

Glacier

ChouteauTeton

Toole

Cascade

Meagher

Lewis & Clark

Liberty

Pondera

Broadwater

JeffersonDeer Lodge

Lincoln

Gallatin

µ=1.09 µ=0.40

µ=0.63

µ=0.63

µ=0.34

µ=0.67

µ=0.66

µ=0.67µ=0.21

µ=0.22

µ= 0.09

µ=1.45

µ=0.37

µ=0.38µ=0.66

µ=0.38 µ=0.89

µ=0.60

µ=1.14

µ=0.24

µ=0.25

µ=1.07

µ=1.75

µ=0.80

µ=2.20µ=0.90

µ=0.13

µ=0.36

µ=0.29

µ=0.62µ=0.18

µ=0.22

µ=0.81

µ=0.33

µ= 0.55

µ=0.15

µ=4.42

µ=0.17µ=2.48

µ=0.47

µ=0.49

µ=0.51

µ=2.31

µ=0.20

µ=0.46

µ=1.25

µ=0.27

µ=0.45

µ=0.48µ=0.84

µ=0.74

µ=0.37µ=1.24

µ=0.79

µ= 0.24

Beaverhead

µ= 2.06

MT PRAMS Oral Health QuestionMT PRAMS Oral Health Question

This question is about the care of your teeth during your most recent pregnancy. For each thing, circle Y (Yes) if it is true or circle N (No) if it is not true.

a. I need to see a dentist for a problem Yes (36.2%)

b. I went to a dentist or dental clinicNo (40.8%)

c. A dental or other health care worker talked to me about how to care for my teeth and gumsNo (37.5%)

Oral Health Inter-state Comparisons Oral Health Inter-state Comparisons

PRAMS Comparisons of Oral Health for Colorado1 and Montana2

Prevalence Rates and 95% Confidence Intervals

0 10 20 30 40 50 60 70 80 90

100

1

Pe r cen t age

Dental Problems - CO Dental Problems - MT Visited dentist - CO Visited dentist - MT Dental care talk - CO Dental care talk - MT

1 Colorado PRAMS was a 5-year study with estimates generated in 2000

2 Montana PRAMS was a 3-year point-in-time study with estimates generated in 2002

• Colorado PRAMS’ Oral Health was highly comparable to Montana PRAMS’ Oral Health

• Disparities exist between the two states for Needing to Visit the Dentist, with Montana mothers reporting significantly higher percentages than Colorado mothers (11.09% difference, Montana PRAMS 36.20%)

Oral Health Inter-state Comparisons Oral Health Inter-state Comparisons

PRAMS Comparisons of Dental Problems for New Mexico, Illinois, and Louisiana - Prevalence Rates1

0 10 20 30 40 50 60 70 80 90

100

Oral Health Indicator

Dental Problems - NM Dental Problems - IL Dental Problems - LA

Pe r cen t age

1 Confidence intervals could not be calculated for other states, due to lack of crude numbers

• Montana PRAMS’ Oral Health exceeds all other reporting states for Needing to Visit the Dentist, with differences exceeding 10% for all comparison states• If confidence intervals for the reported states were similar to Colorado, there would be a significant difference between all reporting states and Montana for the reported variable Needing to Visit the Dentist

MethodologyMethodology

SUDAAN-callable software utilized through SAS 9.13SUDAAN-callable software utilized through SAS 9.13

Cross-checks with SAS 9.1 Survey-callsCross-checks with SAS 9.1 Survey-calls

Quality assurance of dataQuality assurance of data

Independent variables: demographical, social, financial, Independent variables: demographical, social, financial, psychological, and physiological in naturepsychological, and physiological in nature

Outcome variables: Outcome variables: Needed to Visit the Dentist, Talked to Needed to Visit the Dentist, Talked to Dentist/HCW about Dental Care, and Visited the DentistDentist/HCW about Dental Care, and Visited the Dentist

Regional assessments comprised of Eastern, Western and Regional assessments comprised of Eastern, Western and Central Service Area divisionsCentral Service Area divisions

Regional Divisions Map*Regional Divisions Map*

ValleyPhillips

Fergus Garfield

Big Horn

Custer

Rosebud

Carter

McCone

Dawson

Carbon

Prairie

Fallon

Richland

Roosevelt

Yellowstone

Stillwater

Daniels Sheridan

Petroleum

Musselshell

Judith Basin

Sweet Grass

Wheatland

Wibaux


Powder River

Eastern

Madison

Ravalli

Powell

Lake

Missoula

Granite

Mineral

Sanders

Flathead

Western

Silver Bow

Hill

Blaine

Park

Glacier

ChouteauTeton

Toole

Gallatin

Cascade

Meagher

Lewis & Clark

Liberty

Pondera

Broadwater

Central

Jefferson

Sampling:

31% Eastern

34% Central

35% Western

Beaverhead

Deer Lodge

Lincoln

*Regional division designations defined by MT DPHHS

Demographic Characteristics of Montana Resident Birth Mothers

Maternal Characteristics State Total % State Total MT PRAMS Total MT PRAMS % Total

Total 11,045 100.0 1,363 100.0

Maternal Age

< 20 1,277 11.6 287 11.7

20-24 3,155 28.6 202 25.4

25-34 5,347 48.4 442 50.1

35+ 1,263 11.4 114 12.8

Maternal Education

< 12 years 1,623 14.7 211 15.1

12 years 3,672 33.2 349 34.3

> 12 years 5,562 50.4 483 50.6

Marital Status

Married 7,415 67.1 393 68.9

Unmarried 3,624 32.8 652 31.1

Medicaid Status

Medicaid During Pregnancy 2,058 59.0 408 34.7

No Medicaid During Pregnancy 1,430 41.0 626 65.3

Baby’s Birth Weight (Grams)

LBW (< 2500 grams) 758 6.9 54 5.0

NBW (2500+ grams) 10,283 93.1 991 95.0

Prenatal Health Care

1st Trimester 9,190 83.2 770 75.8

2nd Trimester 1,487 13.5 237 21.5

3rd Trimester 242 2.2 16 1.6

No Care 61 0.6 11 1.1

Valley

Phillips

Fergus Garfield

Big Horn

Custer

Rosebud

Carter

McCone

Dawson

Prairie

Fallon

Richland

Roosevelt

Yellowstone

Stillwater

Daniels

PetroleumJudith Basin

Sweet Grass

WheatlandTreasureGolden

Valley

Powder River

Madison

Ravalli

Powell

Lake

Missoula

Granite

Sanders

Flathead

Silver Bow

Hill

Blaine

Park

Glacier

ChouteauTeton

Toole

Meagher

Lewis & Clark

Liberty

Pondera

Broadwater

JeffersonDeer Lodge

Lincoln

Gallatin

Beaverhead

Cascade

Sheridan

Wibaux

Carbon

Musselshell

Mineral

Proportion of Pregnant Women Having a Dental Problem During Pregnancy (PRAMS)

Legend

75.01 to 100.0%

50.01 to 75.00% No Data

25.01 to 50.00%

0.00 to 25.00%

DemographicVariables

SampleDistribution

(%)

Needed tovisit a dentist

Went to visita dentist (=no)

Dentist discussed howto care for teeth (=no)

% yes

p-value

Prevalence Ratio (PR)

95%CI

% no

p-value

PR 95%CI

% no

p-value

PR 95%CI

Maternal Education(n=10,698)

< 12 years

15.09 21.61 <0.0001 3.00 2.03-4.43

16.44 0.0269 1.57 1.05-2.33

15.63

0.4362 1.17 0.79-1.745

12 years 34.33 42.26 <0.0001 2.30 1.68-3.16

35.47 0.1549 1.24 0.92-1.685

34.09

0.9675 0.99 0.73-1.355

> 12 years

50.58 36.13 Reference Group

48.09 Reference Group

50.28

Reference Group

Paternal Education(n=9,610)

< 12 years

9.36 12.97 <0.0001 2.73 1.63-4.56

10.48 0.0775 1.5913 0.95-2.665

10.77

0.1025 1.5813 0.91-2.745

12 years 39.93 50.58 <0.0001 2.32 1.68-3.21

42.31 0.0394 1.37 1.02-1.86

38.94

0.7260 0.9513 0.70-1.295

> 12 years



50.29

Reference Group

GeographicArea

(n=10,720)

Eastern 31.31 35.67 0.0175 1.52 1.08-2.15

32.79 0.3222 1.18

0.85-1.655

31.82

0.6787 1.07 0.77-1.515

Western 34.46 34.31 0.2353 0.81 0.87-1.74

34.30 0.5800 1.10

0.79-1.515

34.78

0.5602 1.10 0.79-1.545

Central 34.23 30.02 Reference Group


33.40

Reference Group

Marital Status

(n=10,720)

Other 31.08 42.66 <0.0001 2.25 1.68-3.02

32.62 0.1074 1.27

0.95-1.715

31.37

0.8108 1.04 0.77-1.395

Married 68.92 57.34 Reference Group


68.63

Reference Group

There were no significant associations between oral health talks and these demographic variables.

Demographics AnalysesDemographics Analyses

There were no significant associations between visiting the dentist and these demographic variables.

Pre-pregnancy Medicaid

(n=10,694)

Yes 8.85 14.79 <0.0001 2.94 1.81-4.78

9.01 0.6518 1.12 0.68-1.855

7.62 0.1369 0.69 0.43-1.125

No 91.15 85.21 Reference Group



Pre-pregnancy Insurance(n=10,702)

No 39.55 55.54 <0.0001 2.81 2.11-3.74

44.29 <0.0001 1.77 1.33-2.35

41.80 0.0187 1.41 1.06-1.88

Yes 60.45 44.46 Reference Group



People per Room in

Home(n=10,489)

1+ People

10.07 13.32 0.0187 1.74 1.10-2.77

10.63 0.4115 1.22 0.76-1.975

10.38 0.6339 1.12 0.70-1.805

0-1 people




Previous Live Births (n=10,581)

Yes 61.46 66.94 <0.0001 1.45 1.33-1.57

60.06 0.2825 0.86 0.66-1.135

59.18 0.0976 0.80 0.60-1.045





SampleDistribution

(%)




% yes

p-value


95%CI

% no

p-value

PR 95%CI

% no

p-value

PR 95%CI

There were no significant associations between these oral health measures and these demographic variables.

Abuse Before Pregnancy(n=10,660)

Yes 8.82 13.96 0.0003 2.40 1.49-3.85

10.86 0.0228 1.79 1.08-2.96

10.32 0.1390 1.47 0.88-2.455




Abuse During

Pregnancy(n=10,662)

Yes 5.05 6.58 0.1547 1.54 0.85-2.785

6.38 0.0179 2.18 1.14-4.15

5.80 0.2344 1.50 0.77-2.945




Smoking Before

Pregnancy(n=10,297)

Yes 29.68 41.64 <0.0001 2.36 1.74-3.20

32.38 0.0096 1.50 1.10-2.03

32.44 0.0067 1.54 1.13-2.11




Smoking During

Pregnancy(n=10,509)

Yes 15.87 24.81 <0.0001 2.65 1.83-3.84

18.37 0.0072 1.70 1.15-2.49

18.47 0.0018 1.90 1.27-2.83






Smoking After

Pregnancy(n=10,518)

Yes 20.84 31.49 <0.0001 2.58 1.85-

3.59

23.85 0.0022 1.73 1.22-2.44

22.84 0.0179 1.54 1.08-2.19




Drinking During

Pregnancy(n=10,519)

Yes 6.78 6.57 0.8735 0.95 0.54-1.705

8.73 0.0165 2.06 1.14-3.72

8.93 0.0045 2.52 1.33-4.77



91.07 Reference GroupDemographic Characteristics associated with heightened risk of reporting a perceived dental

problem:

• Younger women

• Women with maternal education ≤ 12 years

• Women whose partners had ≤ 12 years of education

• Women living in Eastern Montana

• Unmarried women

• Women with pre-pregnancy Medicaid

• Women with no pre-pregnancy insurance (Medicaid excluded)

• Women with more than one person per room in the home

• Women with at least one previous live birth

• Women with abuse before pregnancy

• Women who smoked before, during, and after pregnancy


SampleDistribution

(%)




% yes

p-value


95%CI

% no

p-value

PR 95%CI

% no

p-value

PR 95%CI

However...However...

When When Visiting the DentistVisiting the Dentist outcomes were assessed, some of outcomes were assessed, some of the same demographic characteristics held steadfast in their the same demographic characteristics held steadfast in their associations, including:associations, including:

Women with maternal education < 12 years Women with maternal education < 12 years

Women with partners with education = 12 yearsWomen with partners with education = 12 years

Women with no pre-pregnancy insurance (Medicaid excluded)Women with no pre-pregnancy insurance (Medicaid excluded)

Women abused before pregnancyWomen abused before pregnancy

Women who smoked before, during or after pregnancyWomen who smoked before, during or after pregnancy

Women having pre-pregnancy Medicaid in Eastern MontanaWomen having pre-pregnancy Medicaid in Eastern Montana

These findings suggest women with these characteristics not These findings suggest women with these characteristics not only had a heightened risk of having a perceived dental only had a heightened risk of having a perceived dental problem, but they were also less likely to visit a dentist.problem, but they were also less likely to visit a dentist.

Additionally...Additionally...

Newly associated maternal demographic characteristics Newly associated maternal demographic characteristics include:include:

Abuse during pregnancyAbuse during pregnancy

Drinking during pregnancyDrinking during pregnancy

Maternal characteristics still associated with Maternal characteristics still associated with Talked with Talked with Dentist/HCW about Oral Health CareDentist/HCW about Oral Health Care include: include:

Women with no pre-pregnancy insurance (Medicaid excluded)Women with no pre-pregnancy insurance (Medicaid excluded)

Women who smoked before, during, or after pregnancyWomen who smoked before, during, or after pregnancy

Women who drank during pregnancyWomen who drank during pregnancy

Demographic Findings...Demographic Findings...

These findings suggest a large number of high-risk demographic These findings suggest a large number of high-risk demographic characteristics may predispose mothers to having a perceived characteristics may predispose mothers to having a perceived dental problem during pregnancydental problem during pregnancy

However, only a select few of these characteristics were associated However, only a select few of these characteristics were associated with inhibited visits to the dentist, including three new associations with inhibited visits to the dentist, including three new associations with no prior affiliation with with no prior affiliation with Needing to Visit the DentistNeeding to Visit the Dentist

Regional Divisions were no longer significant for Regional Divisions were no longer significant for Needing to Visit the Needing to Visit the DentistDentist, which may be contradictory to other Access to Care reports. , which may be contradictory to other Access to Care reports. However, pre-pregnancy Medicaid participants (subgroup) However, pre-pregnancy Medicaid participants (subgroup) continued to have access to care issues during pregnancy for continued to have access to care issues during pregnancy for Needing to Visit the DentistNeeding to Visit the Dentist

Lack of pre-pregnancy insurance (Medicaid-excluded) and all levels Lack of pre-pregnancy insurance (Medicaid-excluded) and all levels of smoking are the only demographic characteristics reported which of smoking are the only demographic characteristics reported which demonstrated risk at every level of PRAMS oral health surveillancedemonstrated risk at every level of PRAMS oral health surveillance

Additional Demographic FindingsAdditional Demographic Findings

Though the results suggest women who drank during pregnancy Though the results suggest women who drank during pregnancy were less likely to have a perceived dental problem, they were also were less likely to have a perceived dental problem, they were also less likely to visit a dentist or ask about oral health care. However, less likely to visit a dentist or ask about oral health care. However, underreporting may be an issue and may have biased these results.underreporting may be an issue and may have biased these results.

These findings should help target the highest risk subgroups of These findings should help target the highest risk subgroups of Montana mothers, to implement intervention and prevention with Montana mothers, to implement intervention and prevention with appropriate oral health strategiesappropriate oral health strategies

These associations/findings may be proxies for low SES or other These associations/findings may be proxies for low SES or other high-risk characteristicshigh-risk characteristics

EasternWestern

Central

EasternWestern

Central

Population per Dentist Ratios

Montana, 2004

1000 - 1999

2000 - 3999

4000 - 13000

No dentist

Number of People Per Dentist

Poor Birth OutcomesPoor Birth Outcomes

ExposureVariables

SampleDistribution (%)7

Low BirthWeight

Infant Admitted To ICU

% yes

p-value


95%CI

% yes

p-value

PR 95%CI

Needed to Visit the Dentist

(n=10,376)

Yes 36.19 52.11 0.0245 1.99 1.09-3.63 50.47 0.0098 1.90 1.17-3.08



Visited the Dentist

(n=10,421)

No 59.23 60.29 0.8847 1.05 0.56-1.965 54.68 0.4308 0.82 0.51-1.375



Talked with the Dentist

(n=10,256)

No 62.49 60.73 0.8077 0.93 0.49-1.745 65.11 0.6370 1.13 0.68-1.895



• Reported Needing to Visit the Dentist was correlated with both low birth weight (<2500 grams) and NICU admission outcomes

• The association suggests women who perceived a dental problem during pregnancy had 99% more occurrences of low birth weight outcomes and 90% more occurrences of NICU admissions than those women not reporting a dental problem during pregnancy

There were no significant associations between these oral health measures and these birth outcome variables.

Maternal Morbidity AnalysesMaternal Morbidity Analyses

ExposureVariables

SampleDistribution

(%)7

Bedrest Hospitalization > 7 days Hospitalization from 1-7 days

% yes

p-value


95%CI

% yes

p-value PR

95%CI

% yes

p-value PR

95%CI


(n=6,602)

Yes 36.19 40.38 0.9796 1.00 0.68-1.465

53.60 0.2721 1.72 0.65-4.585

41.38 0.8526 1.05 0.65-1.675




Visited the Dentist

(n=6,586)

No 59.23 59.71 0.8338 1.04 0.71-1.535

48.07 0.3595 0.64 0.24-1.685

59.43 0.9277 1.02 0.64-1.635




Talked with the Dentist(n=6,499)

No 62.49 67.34 0.1935 1.30 0.88-1.945

63.64 0.9502 1.03 0.38-2.835

60.62 0.6317 0.89 0.56-1.435




ExposureVariables

SampleDistribution

(%)7

Hospitalization < 1 day Premature Rupture of Membranes Cervix Sewn Shut

% yes

p-value


95%CI

% yes

p-value PR

95%CI

% yes

p-value PR

95%CI


(n=6,602)

Yes 36.19 48.07 0.0124 1.59 1.11-2.28

33.18 (n=10349)

0.7113 0.87 0.41-1.845

28.46 (n=10367)

0.4939 0.70 0.25-1.975




Visited the Dentist

(n=6,586)

No 59.23 65.44 0.0320 1.50 1.04-2.16

74.21 (n=10394)

0.0790 2.03 0.92-4.485

60.79 (n=10412)

0.8906 1.07 0.41-2.835





No 62.49 71.00 0.0066 1.70 1.16-2.50

72.11 (n=10229)

0.2350 1.58 0.74-3.375

62.62 (n=10246)

0.9880 0.99 0.39-2.605




There were no significant associations between these oral health measures and these maternal morbidity variables.


Maternal Morbidity AnalysesMaternal Morbidity Analyses

ExposureVariables

SampleDistribution

(%)7

Car Accidents Nausea Diabetes

% yes

p-value PR

95%CI

% yes

p-value PR

95%CI

% yes

p-value PR

95%CI


(n=10,371)

Yes 36.19 63.79 0.0359 3.16 1.08-9.27

44.44 0.0054 1.58 1.14-2.17

43.27 (n=10354)

0.3052 1.37 0.75-2.515




Visited the Dentist

(n=10,416)

No 59.23 45.44 0.2536 0.57 0.22-1.505

59.08 0.9652 0.99 0.72-1.365

59.67 (n=10399)

0.9546 1.02 0.55-1.895





No 62.49 55.92 0.5822 0.76 0.28-2.035

60.96 0.6109 0.92 0.67-1.275

61.40 (n=10233)

0.8703 0.95 0.52-1.755





• Only Hospitalization < 1 day was significantly associated with all three of the PRAMS oral health indicators, with odds ratios ranging from 1.50 to 1.70

• This association may be a proxy for SES and/or Access to Care, as short duration hospitalization during pregnancy correlated with lack of oral health prevention and intervention

• Needed to Visit the Dentist was associated with both Car Accidents and Nausea

Oral Health ModelingOral Health Modeling

Used a cumulative stressor index, based on the total number of stressors Used a cumulative stressor index, based on the total number of stressors experienced by the mother 12 months before pregnancy – similar to the experienced by the mother 12 months before pregnancy – similar to the threshold research done by Whitehead et al. from the CDCthreshold research done by Whitehead et al. from the CDC

Stressors include home disputes and problems, familial drug abuse or illness, and monetary Stressors include home disputes and problems, familial drug abuse or illness, and monetary problems or joblessnessproblems or joblessness

Modeled the linearity of the cumulative stressor index with the binary outcome Modeled the linearity of the cumulative stressor index with the binary outcome of having a perceived dental problem during pregnancyof having a perceived dental problem during pregnancy

Used simple, unconditional logistic regression in both SAS SURVEYLOGISTIC Used simple, unconditional logistic regression in both SAS SURVEYLOGISTIC and SUDAAN RLOGISTand SUDAAN RLOGIST

μμ= 2.15 (95% CI=2.01 - 2.29), Range= 0 to 12 Cumulative Stressors= 2.15 (95% CI=2.01 - 2.29), Range= 0 to 12 Cumulative StressorsLogit Odds (Ŷ=1)= -1.3360 + 0.3375 (Logit Odds (Ŷ=1)= -1.3360 + 0.3375 (Cumulative StressorsCumulative Stressors) + 0.0429 () + 0.0429 (Standard ErrorStandard Error))Odds ratio=1.401 (95% CI= 1.29 - 1.52)Odds ratio=1.401 (95% CI= 1.29 - 1.52)

This finding suggests pregnant women who selected listed stressors had a 40% This finding suggests pregnant women who selected listed stressors had a 40% higher prevalence of a perceived dental problem during pregnancy than women higher prevalence of a perceived dental problem during pregnancy than women who did not report the stressors 12 months before pregnancywho did not report the stressors 12 months before pregnancy

For every two additional stressors, the odds of having a dental need increase For every two additional stressors, the odds of having a dental need increase 96.28%96.28%

C-statistic=0.678C-statistic=0.678

Periodontal Disease and Periodontal Disease and Maternal NauseaMaternal Nausea

Li et al. suggests, in the publication “Systemic Diseases Caused by Li et al. suggests, in the publication “Systemic Diseases Caused by Oral Infection”, maternal nausea may be associated with maternal Oral Infection”, maternal nausea may be associated with maternal dental problems during pregnancy. dental problems during pregnancy.

Initial, crude associations from maternal morbidity and Initial, crude associations from maternal morbidity and Needed to Needed to Visit the DentistVisit the Dentist variables suggest there is a significant relationship, variables suggest there is a significant relationship, when reporting PRAMS mothers were analyzedwhen reporting PRAMS mothers were analyzed

Additional investigation is warrantedAdditional investigation is warranted

Oral Health ModelingOral Health Modeling

ModelVariables6

Y-Intercept

BetaCoefficients

Adjusted Odds

Ratios

95%CI’s

R-Squared/C-

Statistic Values

-1.5283

Maternal Nausea 0.3745 1.45 1.03 - 2.05

Smoking 3 Months Before Pregnancy

0.7503 2.12 1.51 - 2.97

Medical Insurance (YES)/(NO)

-0.8239 0.44/2.28 0.32 - 0.60/1.66 - 3.13

Previous Live Birth 0.4866 1.63 1.19 - 2.22 AdjR2=0.61/C=0.67

6 This model was selected based on the most parsimonious model with the best-fitting independent variables being selected through forward selection methods with an alpha of 0.20 and a final selection using manual, stepwise methods and an alpha of 0.05. Interactions were assessed for after the former forward selection method was utilized. Confounders were not assessed for due to Simpson’s Paradox existing with the variable “insure” when stratification was done for interaction. Sample size was the issue for the paradox, therefore, adjusted odds ratios from the controlled model were used for this report.

InterpretationInterpretation

The adjusted odds ratio for the association between maternal The adjusted odds ratio for the association between maternal nausea and dental need is significant at 1.45, suggesting there is a nausea and dental need is significant at 1.45, suggesting there is a 45% difference in dental need prevalence between women reporting 45% difference in dental need prevalence between women reporting maternal nausea and those not reporting maternal nausea during maternal nausea and those not reporting maternal nausea during pregnancypregnancy

The 0.13 or 13% risk difference in the crude and adjusted odds ratio The 0.13 or 13% risk difference in the crude and adjusted odds ratio for maternal nausea is attributable to the other maternal factors for maternal nausea is attributable to the other maternal factors included in the model: having a previous live birth, lacking pre-included in the model: having a previous live birth, lacking pre-pregnancy insurance, and smoking 3 months before pregnancypregnancy insurance, and smoking 3 months before pregnancy

However, after controlling other maternal factors, there is still a However, after controlling other maternal factors, there is still a significant association between maternal nausea and significant association between maternal nausea and Needed to Needed to Visit the Dentist, Visit the Dentist, supporting some of the findings of Li et al.supporting some of the findings of Li et al.

The data supports the recommendations for dental health The data supports the recommendations for dental health prevention information being disseminated early in pregnancy, to prevention information being disseminated early in pregnancy, to counteract the risk associated with maternal nauseacounteract the risk associated with maternal nausea

Additional FindingsAdditional Findings

Self-reported Self-reported Needed to Visit the DentistNeeded to Visit the Dentist appears to be highly appears to be highly associated with both reported admissions to NICU and low birth associated with both reported admissions to NICU and low birth weight outcomes, confirming the findings of Li et al. regarding poor weight outcomes, confirming the findings of Li et al. regarding poor infant outcomes and poor oral healthinfant outcomes and poor oral healthCumulative modeling of maternal stressors during pregnancy Cumulative modeling of maternal stressors during pregnancy suggested heightened risk of dental need, confirming similar research suggested heightened risk of dental need, confirming similar research by Whitehead et al.by Whitehead et al.Modeling of maternal nausea during pregnancy also suggested Modeling of maternal nausea during pregnancy also suggested heightened risk of dental need, when other factors were controlled for heightened risk of dental need, when other factors were controlled for in the modelin the modelFew maternal morbidity variables were significantly associated with Few maternal morbidity variables were significantly associated with the oral health indicators collected by Montana PRAMS, negating the the oral health indicators collected by Montana PRAMS, negating the publication by Li et al. that suggested PRM, pre-term labor, maternal publication by Li et al. that suggested PRM, pre-term labor, maternal diabetes and other maternal problems were associated with poor oral diabetes and other maternal problems were associated with poor oral health during pregnancyhealth during pregnancyHowever, indirect pathways of causation may play an integral part in However, indirect pathways of causation may play an integral part in maternal susceptibility to poor infant outcomesmaternal susceptibility to poor infant outcomesFurther research is needed to fully understand the relationship of Further research is needed to fully understand the relationship of dental need, specifically oral health problems such as periodontal dental need, specifically oral health problems such as periodontal disease, and poor infant outcomesdisease, and poor infant outcomes

Mapping the indirect and direct pathways of how poor oral health is Mapping the indirect and direct pathways of how poor oral health is affected by maternal nausea is important, due to associations with the affected by maternal nausea is important, due to associations with the weight and health of infants at birthweight and health of infants at birth

What Can Be Done?What Can Be Done?Step 1: Understand/Identify who is most at riskStep 1: Understand/Identify who is most at risk

Using data to make sound risk assessmentsUsing data to make sound risk assessments Refer to “checklist” of risk factorsRefer to “checklist” of risk factors Counsel client on potential risk of negative outcome, due to risk assessmentCounsel client on potential risk of negative outcome, due to risk assessment

Step 2: Intervene, where applicableStep 2: Intervene, where applicable Give referrals to area dentists/PhDs/healthcare workers for counseling and interventionGive referrals to area dentists/PhDs/healthcare workers for counseling and intervention Give out dental floss and new toothbrushes, coupons for fluoride rinsesGive out dental floss and new toothbrushes, coupons for fluoride rinses Network and collaborate with area stakeholders such as the Department of Environmental Quality Network and collaborate with area stakeholders such as the Department of Environmental Quality

(DEQ), the Environmental Protection Agency (EPA), and state/county health departments to insure (DEQ), the Environmental Protection Agency (EPA), and state/county health departments to insure optimal levels of fluoridation during pregnancy through assessment and intervention of household optimal levels of fluoridation during pregnancy through assessment and intervention of household water supplywater supply

Step 3: EDUCATE, EDUCATE, EDUCATE Step 3: EDUCATE, EDUCATE, EDUCATE Train non-dental and medical health professionals on the value of oral health during pregnancy and Train non-dental and medical health professionals on the value of oral health during pregnancy and

how to screen for basic conditions, such as caries formation, periodontal disease, and “mottled teeth” how to screen for basic conditions, such as caries formation, periodontal disease, and “mottled teeth” Inform pregnant clients of the importance of good oral health during pregnancyInform pregnant clients of the importance of good oral health during pregnancy Educate clients on the effects of proper nutrition on good oral healthEducate clients on the effects of proper nutrition on good oral health Educate clients on signs of gingivitis, periodontal disease, and fluorosisEducate clients on signs of gingivitis, periodontal disease, and fluorosis Explain the risk of bacteria transference after birth to clients highlighting preventive effortsExplain the risk of bacteria transference after birth to clients highlighting preventive efforts Disseminate information/education through available resources, such as WIC distributions to clients Disseminate information/education through available resources, such as WIC distributions to clients

and distributions to physicians and hospitals/clinicsand distributions to physicians and hospitals/clinics

Step 4: Resources for changeStep 4: Resources for change Empowering personal change=enabling personal controlEmpowering personal change=enabling personal control Give resources for education and informationGive resources for education and information Direct collaboration of multiple sectors within your community – encase client with supportDirect collaboration of multiple sectors within your community – encase client with support

LimitationsLimitations

Montana PRAMS is a self-reported surveyMontana PRAMS is a self-reported survey

Additionally, partner characteristics were not self-reportedAdditionally, partner characteristics were not self-reported

Recall bias may be an issue, especially for socially stigmatizing Recall bias may be an issue, especially for socially stigmatizing behaviorsbehaviors

Minorities were not expressly over-sampled and minority stratification on Minorities were not expressly over-sampled and minority stratification on maternal characteristics could not be utilizedmaternal characteristics could not be utilized

In some instances, missing values were larger than 10%In some instances, missing values were larger than 10%

Confidence intervals for comparison states could not always be Confidence intervals for comparison states could not always be calculated calculated

Measures of association were often crude, with binary variable levelsMeasures of association were often crude, with binary variable levels

Data quality could only be checked post-hocData quality could only be checked post-hoc

Inferences were made regarding the nature of the oral health indicatorsInferences were made regarding the nature of the oral health indicators

Logistic regression assumptions were only partially tested Logistic regression assumptions were only partially tested

Rural well water could not be ascertained for this presentationRural well water could not be ascertained for this presentation

References and ResourcesReferences and Resources

Gaffield, M., et al. Oral Health During Pregnancy: An Analysis of Information Gaffield, M., et al. Oral Health During Pregnancy: An Analysis of Information Collected by the Pregnancy Risk Assessment Monitoring System. JADA. Collected by the Pregnancy Risk Assessment Monitoring System. JADA. 2001; 132: 1009-16.2001; 132: 1009-16.

Offenbacher, S., and Slade, G. Role of periodontitis in systemic health: Offenbacher, S., and Slade, G. Role of periodontitis in systemic health: Spontaneous pre-term birth. Journal of Dental Education. 1998: 62 (10): 852-Spontaneous pre-term birth. Journal of Dental Education. 1998: 62 (10): 852-58.58.

Whitehead, Nedra, et al. Exploration of Threshold Analysis in the Relation Whitehead, Nedra, et al. Exploration of Threshold Analysis in the Relation between Stressful Life Events and Pre-term Labor. American Journal of between Stressful Life Events and Pre-term Labor. American Journal of Epidemiology. 2002; 155 (2): 117-24.Epidemiology. 2002; 155 (2): 117-24.

Li, Xiaojing, et al. Systemic Diseases Caused by Oral Infection. Clinical Li, Xiaojing, et al. Systemic Diseases Caused by Oral Infection. Clinical Microbiology Reviews. 2000; 13(4);547-58.Microbiology Reviews. 2000; 13(4);547-58.

Presentation by Dr. Wendy Mouradian, MD, MS. Montana’s Spring Public Presentation by Dr. Wendy Mouradian, MD, MS. Montana’s Spring Public Health Conference. 2005.Health Conference. 2005.

National Institute of Dental and Craniofacial Research. 2000. National Institute of Dental and Craniofacial Research. 2000. Oral Health in Oral Health in America: A Report of the Surgeon General – Executive Summary. America: A Report of the Surgeon General – Executive Summary. Rockville, Rockville, MD: National Institute of Dental and Craniofacial Research.MD: National Institute of Dental and Craniofacial Research.

References and ResourcesReferences and Resources

Montana Behavioral Risk Factor Surveillance Survey (BRFSS), 2002 Survey Montana Behavioral Risk Factor Surveillance Survey (BRFSS), 2002 Survey Data.Data.

Montana Central Tumor Registry, 2005 Data.Montana Central Tumor Registry, 2005 Data.

Zeeman, GG, Veth EO, Dennison DK. 2001. Periodontal disease: Implications Zeeman, GG, Veth EO, Dennison DK. 2001. Periodontal disease: Implications for women’s health. for women’s health. Obstetrical & Gynecological SurveyObstetrical & Gynecological Survey 56(1): 43-49. 56(1): 43-49.

Jeffcoat MK, Geurs NC, Reddy MS, Cliver Sp, Goldenberg RL, Hauth Jc. 2001. Jeffcoat MK, Geurs NC, Reddy MS, Cliver Sp, Goldenberg RL, Hauth Jc. 2001. Periodontal infection and preterm birth: Results of a prospective study. Periodontal infection and preterm birth: Results of a prospective study. Journal Journal of the American Dental Association of the American Dental Association 132(7): 875 – 880.132(7): 875 – 880.

DPHHS School Oral Health Report, 2002 – 2004 Data.DPHHS School Oral Health Report, 2002 – 2004 Data.

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