Background

Public Health Significance of HDP

Theoretical Framework

Air Pollution and HDP

Neighborhood SES and HDP

Racial Disparities in HDP

Knowledge Gap

Research Objectives

Hypertensive Disorders of Pregnancy (HDP)

A common pregnancy complication (up to 10%)

Classified into four categories:

• Chronic hypertension
• Gestational hypertension
• Preeclampsia-eclampsia
• Preeclampsia superimposed on chronic hypertension

Linked to adverse health outcomes in both mothers and infants

Theoretical Framework

A Socio-Ecological Model (SEM) of Factors Influencing HDP

Air Pollution and HDP

Air pollution and adverse birth outcomes

Air pollution and hypertension in the general population

Potential biological mechanisms:

• Increased oxidative stress
• Lipid peroxidation
• Inflammation
• Endothelial dysfunction
• Autonomic imbalance
• Altered blood rheology

Existing literature:

• Inconsistent results
• Sparsely located stationary air monitors
• Critical window of exposure is unknown

Chemical Environment

Neighborhood SES and HDP

Neighborhood SES and adverse birth outcomes

Neighborhood SES and hypertension in the general population

Existing literature:

• Inconsistent results

               Social differences

               Different SES categories examined

• Neighborhood SES is multifaceted

               A variety of indices used in previous studies

               Hard to interpret the results and to guide interventions

Social Environment

Racial Disparities in HDP

Increasingly large racial disparities in HDP

Racial residential segregation

• The fundamental cause of racial disparities
• Linked to adverse birth outcomes

Little is known about the factors contributing to racial disparities in HDP

Knowledge Gaps

Very few studies and inconsistent results

 

Critical window of exposure to air pollution during pregnancy is unknown

 

Individual neighborhood SES characteristic predictive of HDP is unknown

 

How neighborhood environment contributes to racial disparities in HDP is unknown

Ozone and HDP in Florida: Identifying Critical Windows of Exposure

Introduction

O₃ is the air pollutant of the greatest concern to the state of Florida

 

Recent meta-analyses suggest an overall positive association between ozone and HDP

 

Limitations in existing literature:

• Sparsely located stationary air monitors
• Critical window of exposure to O₃ is unknown

Research Objectives

• To investigate the association between O₃ exposure during pregnancy and hypertensive disorders of pregnancy.
  Hypothesis 1.1: Exposure to O₃ during the first two trimesters of pregnancy is associated with hypertensive disorders of pregnancy.
  Hypothesis 1.2: Early pregnancy is the most critical window of exposure.

Study Sample

Data source: Florida Vital Statistics Birth Record data

Outcome Assessment

Diagnoses of prepregnancy hypertension, gestational hypertension or preeclampsia, and eclampsia were collected

 

The restricted definition of HDP was used in this study, which only includes:

• Gestational hypertension
  the development of hypertension after 20 weeks of pregnancy
• Preeclampsia
  the new onset of hypertension and proteinuria after 20 weeks of pregnancy
• Eclampsia
  the onset of convulsions

Ozone Exposure Assessment

Data: The hierarchical Bayesian space-time statistical modeled (HBM) data from the National Environmental Public Health Tracking Network (2005-2008)

• Daily
• 12km×12km

 

Exposure windows:

• Predefined: trimester 1 only (1-13 weeks), trimester 2 only (14-26 weeks), and trimesters 1 and 2 (1-26 weeks)
• Weekly

Covariates

Age: <20, 20-24, 25-29, 30-34, 35-39, or ≥40 years old

Race/ethnicity: non-Hispanic White, non-Hispanic Black, Hispanic, or others

Education: <high school, high school or equivalent, or >high school

Marital status: married or not married

Pregnancy smoking status: yes or no

Pre-pregnancy BMI: underweight, normal, overweight, or obese

Season of conception: warm (June-November) or cool (December-May)

Year of conception: 2005, 2006, or 2007

Statistical Analyses

Predefined windows of exposure:

• Trimester 1 only, trimester 2 only, and both trimesters 1 and 2
• Logistic regression models
• Both an unadjusted model and an adjusted model controlling for covariates
• ORs with 95% CIs for each 5 ppb increase in O₃

​

Identification of critical window of exposure:

• Weekly
• Constrained distributed lag models
  The associations between HDP and each of the 26 weekly O₃ exposures was examined controlling for other weekly O₃ exposures.
  Constrained the 26 weekly specific effect estimates to follow the shape of a natural cubic spline with a knot at lag 13

Results

Results

Results

Discussion

A consistent pattern of elevated odds of HDP with increased exposure to O₃ during the first two trimesters.

 

Early pregnancy was the most critical window for O₃ exposure during pregnancy.

 

Consistent with pooled estimates from meta-analyses

• First trimester exposure: OR=1.05, 95% CI: 1.02, 1.06 for each 5 ppb increase in O₃
• No significant association for second trimester exposure

Discussion

Potential biological mechanism:

• Oxidative stress
• Lipid peroxidation
• Inflammation
• Endothelial dysfunction
• Autonomic imbalance
• Altered blood rheology

 

The elevated odds ratio observed in early pregnancy:

• Differences in blood pressure patterns during pregnancy
• Vasoconstriction

Discussion

Implications for health interventions:

• Almost impossible to avoid air pollution exposure during one's entire pregnancy period
• Identification of critical exposure window can guide future intervention

 

Strengths:

• Large sample size and high geocoded rate
• High temporal and spatial resolutions of the exposure data
•  Assessed critical windows of exposure

 

Limitations:

• HDP measurements: no diagnosis dates or detailed blood pressure, potential under-diagnoses
• O₃ measurements: no data on residential history, daily mobility and behavior patterns

Neighborhood Socioeconomic Status and HDP in Florida

Introduction

Socioeconomic status (SES) is an important determinant of health.

 

Low neighborhood SES has been linked to increased risks of hypertension in the general population and adverse birth outcomes.

 

Limitations in existing literature:

• Only a few studies examined neighborhood SES and HDP
• All used composite indices and individual neighborhood SES factor predictive of HDP is unknown

Research Objectives

• To examine the association between neighborhood socioeconomic status and hypertensive disorders of pregnancy.

  Hypothesis 2.1: Neighborhood socioeconomic status assessed by the Standardized Neighborhood Deprivation Index is associated with hypertensive disorders of pregnancy.
  Hypothesis 2.2: Individual neighborhood socioeconomic characteristics such as income and poverty are predictive of hypertensive disorders of pregnancy.

Study Sample

Data source: Florida Vital Statistics Birth Record data

All women gave live births in Florida during 2005-2008 (n=917,788)

Residential addresses which could not be geocoded (n=108) or outside Florida (n=4,632) were excluded.

Conception date between January 1, 2005 and December 31, 2007 (n=691,011)

Exclude non-singleton deliveries (n=21,609), pre-pregnancy hypertension (n=10,590), birthweight <500g or >5,000g (n=621), with a gestational age <26 weeks (n=2,662), or missing NDI (n=3,581).

A total of 651,948 women were included.

Outcome Assessment

Diagnoses of prepregnancy hypertension, gestational hypertension or preeclampsia, and eclampsia were collected

 

The restricted definition of HDP was used in this study, which only includes:

• Gestational hypertension
  the development of hypertension after 20 weeks of pregnancy
• Preeclampsia
  the new onset of hypertension and proteinuria after 20 weeks of gestation
• Eclampsia
  the onset of convulsions

Neighborhood SES Assessment

Data: The 2006-2010 American Community Survey

• 17 census-tract level SES characteristics
• Covering 7 different domains:
  Poverty: % HHs in poverty, % HHs earning <$30,000/year, % HHs with no vehicle
  Occupation: % males(females) in management or professional occupations
  Housing: % rented housing, % vacant housing, % renter/owner costs>50% income, median household value
  Employment: % unemployed, % males no longer in work force
  Education: % <high school education
  Racial composition: % non-Hispanic blacks
  Residential stability: % in same residence in the last year, % residents ≥65 years old

 

Neighborhood Deprivation Index (NDI):

• Created using the first factor loadings from PCA
• Categorized into quartiles in census-tract level

Covariates

Age: <20, 20-24, 25-29, 30-34, 35-39, or ≥40 years old

Race/ethnicity: non-Hispanic White, non-Hispanic Black, Hispanic, or others

Education: <high school, high school or equivalent, or >high school

Marital status: married or not married

Pregnancy smoking status: yes or no

Pre-pregnancy BMI: underweight, normal, overweight, or obese

Season of conception: warm (June-November) or cool (December-May)

Year of conception: 2005, 2006, or 2007

Urbanity: urban or rural

Statistical Analyses

NDI:

• Logistic regression models
• Both an unadjusted model and an adjusted model controlling for covariates
• ORs with 95% CIs ​

​

Determination of predictive neighborhood SES characteristics:

• Regularized Logistic regression with l1-penalty (LASSO)
  The parameter λ was tuned by a 10-fold cross-validation based on AUC
• Variables with nonzero coefficients were refitted using the unpenalized Logistic regression model

Results

Results

Results

Discussion

Women living in neighborhoods with lower SES had higher odds of HDP.

 

The following neighborhood characteristics are predictive of HDP:

• Percentage of women in professional occupations
• Percentage of non-Hispanic blacks
• Median household value
• Residential stability
   

Consistent with previous studies:

• Clausen et al. 2006 found that women living in low-income areas had higher rates of preeclampsia than women living in high-income areas.
• Vinikoor-Imler et al. (2012) reported a positive association between neighborhood deprivation and HDP in the US.

Discussion

Implications for health interventions:

• Provides insights into the important characteristics of SES that may inform targeted intervention.
• Identifications of vulnerable population subgroups such as pregnant women living in a low SES neighborhood with a residential instability.

Strengths:

• Large sample size and minimal selection bias
• Assessed neighborhood SES using both a composite index and individual characteristics.

Limitations:

• HDP measurements: no diagnosis dates or detailed blood pressure, potential under-diagnoses.
• Neighborhood SES measurements: low temporal resolution in the exposure data.
• Other potential confounders such as diet.

Racial Disparities in HDP Mediated by Neighborhood Environmental Factors

Introduction

The burden of HDP falls disproportionately on African Americans.

 

There is an increasing trend of racial disparities in HDP.

 

Neighborhood environmental factors such as racial residential segregation, urbanity, neighborhood SES, and O₃ exposure are potential mediators for racial disparities in HDP.

 

Few studies has directly addressed how neighborhood environmental factors contribute to the racial disparities in HDP.

Research Objectives

• To examine the racial disparities in hypertensive disorders of pregnancy and how neighborhood environmental factors mediate the pathways.

  Hypothesis 3.1: African American women have higher risks of hypertensive disorders of pregnancy compared with non-African Americans.
  Hypothesis 3.2: The association between race and hypertensive disorders of pregnancy is mediated by neighborhood environmental factors including O₃ exposure during pregnancy, neighborhood socioeconomic status, urbanity, and racial residential segregation.

Study Sample

Data source: Florida Vital Statistics Birth Record data

All women gave live births in Florida during 2005-2008 (n=917,788)

Residential addresses which could not be geocoded (n=108) or outside Florida (n=4,632) were excluded.

Conception date between January 1, 2005 and December 31, 2007 (n=691,011)

Exclude non-singleton deliveries (n=21,609), pre-pregnancy hypertension (n=10,590), birthweight <500g or >5,000g (n=621), with a gestational age <26 weeks (n=2,662), or missing race/ethnicity (n=14).

A total of 655,515 women were included.

Outcome Assessment

Diagnoses of prepregnancy hypertension, gestational hypertension or preeclampsia, and eclampsia were collected

 

The restricted definition of HDP was used in this study, which only includes:

• Gestational hypertension
  the development of hypertension after 20 weeks of pregnancy
• Preeclampsia
  the new onset of hypertension and proteinuria after 20 weeks of gestation
• Eclampsia
  the onset of convulsions

Racial Residential Segregation Assessment

The spatial measure of neighborhood level racial isolation developed by Anthopolos et al. 2011.

• Census block-group level population count data by race from the 2006-2010 American Community Survey.
   
• 
   
• It can be interpreted as the average percentage of group m in the local environment of r _i as defined by the adjacency matrix.
• Bordering block groups located outside the State of Florida were also included to correct for the edge effects.

 Assessments of Other Mediators and Covariates

Ozone: exposure during the first two trimesters using the HBM data

NDI: the first factor loadings from the PCA on 17 variables
Urbanity: 2010 Census

 

Age: <20, 20-24, 25-29, 30-34, 35-39, or ≥40 years old

Race/ethnicity: non-Hispanic White, non-Hispanic Black, Hispanic, or others

Education: <high school, high school or equivalent, or >high school

Marital status: married or not married

Pregnancy smoking status: yes or no

Pre-pregnancy BMI: underweight, normal, overweight, or obese

Season of conception: warm (June-November) or cool (December-May)

Year of conception: 2005, 2006, or 2007

Statistical Analyses

Determination of racial disparities in HDP:

• Logistic regression models
• Both an unadjusted model and an adjusted model controlling for covariates
• ORs with 95% CIs ​

​

Mediation analyses to determine how neighborhood environmental factors contribute to racial disparities in HDP:

• The Inverse Odds Ratio Weighting (IORW) developed by Nguyen et al. 2015

Mediation Analyses

The IORW avoids the difficulties of specifying a model for the joint conditional density of multiple mediators by using weights to indicate the relationship between exposure and multiple mediators.

 

Standard errors for the estimated direct and indirect effects were derived by using 1,000 bootstrap replications.

Results

Discussion

African American women had significantly higher odds to have HDP compared with non-African American women.

35% of racial disparities in HDP can be explained by the differential exposure to neighborhood environmental factors, including ozone exposure, urbanity, neighborhood SES, and racial residential segregation, between African American women and non-African American women. 

Discussion

Consistent with existing literature:

• Racial residential segregation has been regarded as the fundamental cause of racial disparities in health.
   
• Urbanity, ozone exposure, and neighborhood SES have been linked to HDP.
   
• Studies suggested that the average residential context of African American communities is worse than the worst residential context for Whites.

​

 

 

Discussion

Implications for health interventions:

• Our findings suggest that the improvement on neighborhood environmental factors can greatly reduce the racial disparities in HDP.

• More efforts should be given on neighborhood-level interventions such as:
  The smart growth by The American Planning Association
  The community revitalization initiatives
  “Environmental justice” interventions

​Strengths:

• Large sample size and minimal selection bias
• Assessed how neighborhood environment may contribute to racial disparities in HDP

Limitations:

• HDP measurements
• Exposure assessments
• Other potential confounders

Conclusions

• Determination of Association between O₃ Exposure during the Three Pre-defined Exposure Windows of Pregnancy and HDP

• Identification of Critical Windows of O₃ Exposure during Pregnancy for HDP
   

• Determination of Association between Neighborhood SES and HDP

• Identification of Individual Neighborhood Socioeconomic Characteristics Predictive of HDP
   

• Identification of Racial Disparities in HDP between African Americans and Non-African Americans

• Determination of the Proportions of Racial Disparities in HDP Contributed by Neighborhood Environmental Factors Including O₃ Exposure, Neighborhood SES, urbanity, and Racial Residential Segregation

Limitations and Future Directions

Limitations:

• Measurement errors in the outcome, exposure, and covariates.
• Trade-off between measurement errors and selection biases.
• Lack of individual-level interventions to reduce environmental risk factors of HDP.

 

Future directions:

• Innovative data sources such as remote sensing and satellite imaging  
• mHealth

Acknowledgements

Supervisory Committee:

• Linda B. Cottler, PhD, MPH, FACE, Chair, Department of Epidemiology, UF
• Cindy A. Prins, PhD, MPH, CIC, CPH, Member, Department of Epidemiology, UF
• Barron H. Henderson, PhD, Member, Department of Environmental Engineering Sciences, UF
• Xiaomin Lu, PhD, Member, Department of Biostatistics, UF

Former Research Mentor: Xiaohui Xu, PhD, MD, Department of Epidemiology & Biostatistics, TAMU

Academic Advisors:

• Volker Mai, PhD, MPH, Current Advisor, Department of Epidemiology, UF
• Maria R. Khan, PhD, MPH, Former Advisor, Department of Population Health, NYU

Florida Department of Health

All faculty, staff, and fellow students in the Department of Epidemiology

Thank You!