Birth Outcomes Among U.S. Women With Hearing Loss

Published:September 26, 2016DOI:https://doi.org/10.1016/j.amepre.2016.08.001

      Introduction

      The purpose of this study is to estimate the national occurrence of deliveries in women with hearing loss and to compare their birth outcomes to women without hearing loss.

      Methods

      This study examined the 2008–2011 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project in 2015 to compare birth outcomes in women with hearing loss and without. Birth outcomes included preterm birth and low birth weight. Multivariate regression analyses compared birth outcomes between women with and without hearing loss, controlling for maternal age, racial and ethnic identity, type of health insurance, comorbidity, region of hospital, location and teaching status of the hospital, ownership of the hospital, and median household income for mother’s ZIP code.

      Results

      Of an estimated 17.9 million deliveries, 10,462 occurred in women with hearing loss. In adjusted regression analyses controlling for demographic characteristics, women with hearing loss were significantly more likely than those without hearing loss to have preterm birth (OR=1.28, 95% CI=1.08, 1.52, p<0.001) and low birth weight (OR=1.43, 95% CI=1.09, 1.90, p<0.05).

      Conclusions

      This study provides a first examination of the pregnancy outcomes among women with hearing loss in the U.S. This analysis demonstrates significant disparities in birth outcomes between women with and without hearing loss. Understanding and addressing the causes of these disparities is critical to improving pregnancy outcomes among women with hearing loss.

      Introduction

      Approximately 1% of people in the U.S. aged 18–44 years have hearing loss (HL).

      National Health Interview Survey. QuickStats: percentage of adults* who reported being deaf or having a lot of trouble hearing without a hearing aid, by sex and age group—United States, 2003. www.cdc.gov/mmwr/preview/mmwrhtml/mm5425a5.htm. Accessed December 1, 2015.

      HL can be categorized based on type (i.e., sensorineural, conductive, and mixed); severity (e.g., mild to profound); configuration (e.g., pattern of HL across frequencies); and age of onset.
      • Zazove P.
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      HL is a marginalizing and disabling condition, resulting in various adverse social and health outcomes.
      • Agrawal Y.
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      • Niparko J.K.
      Prevalence of hearing loss and differences by demographic characteristics among U.S. adults: data from the National Health and Nutrition Examination Survey, 1999-2004.
      Unfortunately, individuals who are deaf and hard of hearing are at extremely high risk for significant health disparities and social marginalization.
      • Barnett S M.M.
      • Smith S.R.
      • Pearson T.A.
      Deaf sign language users, health inequities, and public health: opportunity for social justice.
      • McKee M.M.
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      Impact of communication on preventive services among deaf American Sign Language users.
      • Barnett S.
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      Community participatory research with deaf sign language users to identify health inequities.
      • Hauser P.
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      Deaf epistemiology: deafhood and deafness.
      • McKee M.
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      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      • Moreland C.
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      Hearing loss: issues in the deaf and hard of hearing communities.
      • McKee M.M.
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      • Sen A.
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      • Fiscella K.
      Emergency department utilization among deaf American Sign Language users.
      Barriers in language, communication, and culture, along with a general mistrust of the medical community, result in social and healthcare marginalization for many individuals with HL.
      • McKee M.M.
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      Ethical issues in conducting research with deaf populations.
      • Meador H.
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      Health care interactions with deaf culture.

      Stern CSA. DeafDOC.org: health education for the deaf and hard of hearing community, interpreters, and healthcare professionals. http://deafdoc.org. Published 2014. Accessed August 30, 2014.

      • McKee M.
      • Hauser P.
      Deaf epistemology: the juggling of two worlds.
      • Barnett S.
      • McKee M.
      • Smith S.R.
      • Pearson T.A.
      Deaf sign language users, health inequities, and public health: opportunity for social justice.
      The marginalization in health care and society results from cumulative effects of communication and language barriers that reduce the population’s opportunities to benefit from mass media, healthcare messages, healthcare communication, and incidental learning opportunities.
      • McKee M.M.
      • Paasche-Orlow M.K.
      • Winters P.C.
      • et al.
      Assessing health literacy in deaf American Sign Language users.
      • McKee M.M.
      • Moreland C.
      • Atcherson S.R.
      • Zazove P.
      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      Healthcare providers rarely receive training on how to effectively communicate and care for individuals with HL, resulting in poor communication, increased provider frustrations, and changes in healthcare delivery.
      • McKee M.
      • Moreland C.
      • Atcherson S.
      • Zazove P.
      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      • Bainbridge KE W.M.
      Hearing loss in an aging American population: extent, impact, and management.
      • McEwen E.
      • Anton-Culver H.
      The medical communication of deaf patients.
      Individuals with HL can also vary with their communication preferences and cultural affiliations. For example, deaf American Sign Language users identify themselves as a linguistic minority community, with their own unique language and culture.
      • Hauser P.
      • O’Hearn A.
      • McKee M.
      • Steider A.
      • Thew D.
      Deaf epistemiology: deafhood and deafness.
      • McKee M.M.
      • McKee K.
      • Winters P.
      • Sutter E.
      • Pearson T.
      Higher educational attainment but not higher income is protective for cardiovascular risk in deaf American Sign Language (ASL) users.
      • Moreland C.
      • Atcherson S.R.
      • Zazove P.
      • McKee M.M.
      Hearing loss: issues in the deaf and hard of hearing communities.
      • Padden C.
      • Humphries T.
      Inside Deaf Culture.
      They view their HL as a cultural identity, hence their usage of a capitalized “Deaf” versus individuals who consider themselves “hard of hearing” or “deaf.”
      • Peter C.H.
      • Amanda O.H.
      • Michael M.
      • Anne S.
      • Denise T.
      Deaf epistemology: deafhood and deafness.
      Hard of hearing or deaf are more likely than deaf American Sign Language users to prefer communication in English (e.g., lip reading) and the use of hearing augmentation (e.g., hearing aids).
      • McKee M.
      • Moreland C.
      • Atcherson S.
      • Zazove P.
      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      Significant health disparities and health knowledge gaps have been demonstrated in this population across a myriad health conditions.
      • McKee M.M.
      • Barnett S.L.
      • Block R.C.
      • Pearson T.A.
      Impact of communication on preventive services among deaf American Sign Language users.
      • Margellos-Anast H.
      • Estarziau M.
      • Kaufman G.
      Cardiovascular disease knowledge among culturally deaf patients in Chicago.
      • McKee M.M.
      • McKee K.
      • Winters P.
      • Sutter E.
      • Pearson T.
      Higher educational attainment but not higher income is protective for cardiovascular risk in deaf American Sign Language (ASL) users.
      • Heuttel K.L.
      • Rothstein W.G.
      HIV/AIDS knowledge and information sources among deaf and hearing college students.
      • Peinkofer J.R.
      HIV education for the deaf, a vulnerable minority.
      • Wollin J.
      • Elder R.
      Mammograms and Pap smears for Australian deaf women.
      • Woodroffe T.
      • Gorenflo D.W.
      • Meador H.E.
      • Zazove P.
      Knowledge and attitudes about AIDS among deaf and hard of hearing persons.
      • Tamaskar P.
      • Malia T.
      • Stern C.
      • Gorenflo D.
      • Meador H.
      • Zazove P.
      Preventive attitudes and beliefs of deaf and hard-of-hearing individuals.
      People with HL generally have lower income and experience social isolation and poorer physical and mental health.
      • Wallhagen M.I.
      • Strawbridge W.J.
      • Shema S.J.
      The relationship between hearing impairment and cognitive function: a 5-year longitudinal study.
      More importantly, with the advent of childhood immunizations and improved management of early childhood infections, the etiologies of HL for young populations are more likely to be attributable to congenital factors, receipt of care in a neonatal intensive care unit, and genetic etiologies.

      American Speech-Language-Hearing Association. Causes of hearing loss in children. www.asha.org/public/hearing/Causes-of-Hearing-Loss-in-Children. Accessed April 15, 2016.

      These sociodemographic, behavioral, and biological differences are consistent with potential risk factors for preterm and low birth weight in the general literature.
      • Boardman J.D.
      • Powers D.A.
      • Padilla Y.C.
      • Hummer R.A.
      Low birth weight, social factors, and developmental outcomes among children in the United States.
      • Beck S.
      • Wojdyla D.
      • Say L.
      • et al.
      The worldwide incidence of preterm birth: a systematic review of maternal mortality and morbidity.
      Despite these disparities in the health of people with HL and their reduced access to health care, to date there are no population-based studies about pregnancy experiences and outcomes among women with HL. A recent study on pregnancy among women with different disabilities found that women with HL were equally likely to be pregnant compared to other women with and without disabilities.
      • Horner-Johnson W.
      • Darney B.G.
      • Kulkarni-Rajasekhara S.
      • Quigley B.
      • Caughey A.
      Pregnancy among U.S. women: differences by presence, type, and complexity of disability.
      Another study
      • O’Hearn A.
      Deaf women’s experiences and satisfaction with prenatal care: a comparative study.
      on Deaf women’s experiences with prenatal care found that Deaf women were less satisfied with their prenatal care and were more likely to have fewer prenatal visits than hearing women.
      Further research is clearly warranted to document the pregnancy experiences and outcomes of U.S. women with HL. To address some of these research gaps, this study used a nationally representative data set to (1) investigate the number of deliveries occurring in women with HL and (2) compare the percentage of deliveries complicated by adverse birth outcomes in U.S. women with and without HL. Given the elevated risk of poor health among people with HL and their reduced healthcare access,
      • McKee M.M.
      • Moreland C.
      • Atcherson S.R.
      • Zazove P.
      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      • Iezzoni L.I.
      • O’Day B.L.
      • Killeen M.
      • Harker H.
      Communicating about health care: observations from persons who are deaf or hard of hearing.
      the investigators hypothesized that the birth outcomes of deliveries among women with HL would be worse than those of other women.

      Methods

      Data Sample

      The data for this study were derived from the Nationwide Inpatient Sample (NIS) of the Health Care and Cost Utilization Project (HCUP), the largest all-payer, publicly available U.S. inpatient healthcare database. It contains data on approximately 8 million hospital stays each year from about 1,000 hospitals sampled to approximate a 20% stratified sample of U.S. community hospitals. The sample of hospitals was drawn from 46 states and were divided into 60 strata based on geographic region, ownership, location, teaching status, and bed size. Detailed information on the design of the survey is available elsewhere.

      Agency for Healthcare Research and Quality. Introduction to the HCUP Nationwide Inpatient Sample (NIS) 2011. www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2011.jsp#sampling. Published November 2015. Accessed December 12, 2015.

      The NIS contains >100 clinical and nonclinical data elements for each hospital stay, including primary and secondary diagnoses and procedures, admission and discharge status, patient demographic characteristics, hospital characteristics, expected payer, total charges, and length of stay.
      • Houchens R.L.
      • Ross D.
      • Elixhauser A.
      Using the HCUP Nationwide Inpatient Sample to Estimate Trends (Updated for 1988-2004): HCUP Methods Series.
      The NIS does not include unique patient identifiers; thus the unit of analysis is hospital discharge. However, each delivery is associated with only one pregnancy; any woman who delivered more than once in a single calendar year was counted twice. Nevertheless, this situation is uncommon because short interpregnancy intervals that result in women giving birth twice within a 12-month period are relatively rare.
      • Adams M.M.
      • Delaney K.M.
      • Stupp P.W.
      • McCarthy B.J.
      • Rawlings J.S.
      The relationship of interpregnancy interval to infant birthweight and length of gestation among low-risk women, Georgia.
      All delivery-related hospitalizations were included in the analysis. Delivery hospitalizations were identified using the ICD-9-CM codes 640.0–676.9, where the fifth digit is 1 (delivered, with or without mention of antepartum condition) or 2 (delivered, with mention of postpartum complication), or ICD-9-CM 650 (normal delivery). Women with HL were identified from ICD-9-CM codes (Table 1). The control group was identified as any delivery hospitalization among women without HL. Owing to the small number of cases of deliveries in women with HL, the study combined data from 2008 to 2011 to increase the sample size, and hence the power of analysis.
      Table 1Classification of Hearing Loss
      Hearing lossICD-9 codes
      Conductive hearing loss
      Excludes: mixed conductive and sensorineural hearing loss (389.20–389.22).
      389.0
      Sensorineural hearing loss
      Excludes: abnormal auditory perception (388.40–388.44).
      389.1
      Mixed conductive and sensorineural hearing loss389.2
      Deaf nonspeaking, not elsewhere classifiable389.7
      Other specified forms of hearing loss389.8
      Unspecified hearing loss389.9
      a Excludes: mixed conductive and sensorineural hearing loss (389.20–389.22).
      b Excludes: abnormal auditory perception (388.40–388.44).

      Measures

      The main dependent variables included the following birth outcomes: (1) preterm birth
      Birth of an infant before 37 weeks of pregnancy (source: WHO).
      identified using ICD-9-CM code 644.2, 644.20, 644.21, 765.0, or 765.1 and (2) low birth weight
      Birth of an infant weighing <2,500 g (source: WHO).
      (656.5, 656.50, 656.51, 656.53). The main independent variable was the HL status of women with delivery-related hospitalization.
      Model covariates included maternal age; racial and ethnic identity (non-Hispanic white, non-Hispanic black, Hispanic, non-Hispanic other); type of health insurance (private, public, uninsured); comorbidity (having one or more of the comorbidities identified by the Agency for Health Care Research and Quality using standard methods by Elixhauser et al.
      • Elixhauser A.
      • Steiner C.
      • Harris D.R.
      • Coffey R.N.
      Comorbidity measures for use with administrative data.
      ); region of hospital (Northeast, Midwest, South, West); location and teaching status of the hospital (urban teaching, urban non-teaching, rural), ownership of the hospital (public, private); and median household income for mother’s ZIP code (first quartile, $1–$38,999; second quartile, $39,000–$47,999; third quartile, $48,000–$62,999; fourth quartile, ≥$63,000).

      Statistical Analysis

      National estimates of the sample’s sociodemographic characteristics were compared for women with HL and without HL. Unadjusted hospitalizations with adverse birth outcomes were calculated for each group. Chi-square analysis was applied to test the difference in rates in each group. Logistic regression analyses were performed for each dichotomous dependent variable. The model was similar to what has been estimated in previous studies on pregnancy and delivery outcomes.
      • Chakravarty E.F.
      • Khanna D.
      • Chung L.
      Pregnancy outcomes in systemic sclerosis, primary pulmonary hypertension, and sickle cell disease.
      • Chakravarty E.F.
      • Nelson L.
      • Krishnan E.
      Obstetric hospitalizations in the United States for women with systemic lupus erythematosus and rheumatoid arthritis.
      • Kelly V.M.
      • Nelson L.M.
      • Chakravarty E.F.
      Obstetric outcomes in women with multiple sclerosis and epilepsy.
      This study used HL as the main independent variable and adjusted for race/ethnicity, maternal age, household income, health insurance status, commorbidity, region, and hospital location, teaching status, and ownership.
      Logistic regression coefficients and 95% CI were estimated as AORs. Hospital discharge weights were applied to the sample data for all bivariate and multivariate statistical analyses. All estimation procedures were corrected for complex design of the NIS. All analyses were performed in 2015 using Stata, version 14 MP.
      This analysis was approved by the Brandeis University IRB.

      Results

      There were 3,266,577 delivery-associated hospitalizations identified through the HCUP 2008–2011 data. Of these, 1,902 delivery hospitalizations were among women with HL, and 3,264,675 were among women without HL. The national estimates, after application of the sample weights, made up 17,967,659 delivery-associated hospitalizations, including 10,462 among women with HL and 17,957,197 among women without HL. Women with HL were more likely to be white and Hispanic and less likely to be from other racial/ethnic groups than other women (Table 2). Women with HL who delivered were less likely to be aged <18 years and more likely to be aged >34 years compared with other women. Medicare and Medicaid were the most common payers for delivery hospitalizations among women with HL, but private insurance was most common among women without HL. Nearly one in seven of women with HL had their deliveries paid for by Medicare, which was significantly higher than Medicare coverage for women without HL (13.3% vs 0.6%). Women with HL were almost twice more likely to have one or more comorbidities and were also more likely to be admitted to urban teaching hospitals.
      Table 2Description of the Sample of Women With and Without Hearing Loss, NIS, HCUP, 2008–2011
      CharacteristicWomen without HL, n (%) (n=3,264,675)Women with HL, n (%) (n=1,902)Test statistics (F test)
      Racial and ethnic identity5.02***
       Non-Hispanic white1,467,699 (45.0)937 (49.4)
       Non-Hispanic black391,909 (12.1)257 (13.4)
       Hispanic640,596 (19.5)322 (16.8)
       Non-Hispanic other304,255 (9.3)135 (7.2)
       Missing460,216 (14.1)251 (13.2)
      Age group (age in years at admission)8.89***
       <241,088,774 (33.4)579 (30.3)
       25–341,701,490 (52.2)987 (51.9)
       >34471,537 (14.5)335 (17.8)
      Insurance payer type743.60***
       Medicare20,035 (0.6)253 (13.4)
       Medicaid1,412,676 (43.3)810 (42.6)
       Private insurance1,629,797 (50.1)744 (39.3)
       Uninsured197,286 (6.1)92 (4.9)
      Comorbidity
      Comorbidity variable is generated using the AHRQ comorbidity software.64 Patients are considered to have comorbidity if their discharge records show that they have one more of the 29 types of patient comorbidities identified by AHRQ using standard methods by Elixhauser.38 AHRQ, Agency for Healthcare Research and Quality; HCUP, Healthcare Cost and Utilization Project; HL, hearing loss; NIS, nationwide inpatient sample.
      232.5***
       One or more comorbidities778,800 (23.8)761 (40.0)
       No comorbidity2,485,875 (76.2)1,141 (60.0)
      Region of hospital1.36
       Northeast505,269 (15.9)296 (16.2)
       Midwest698,971 (21.6)418 (22.8)
       South1,238,350 (37.9)663 (34.5)
       West822,085 (24.7)525 (27.3)
      Hospital location and teaching status12.72***
       Rural364,844 (11.5)172 (9.2)
       Urban non-teaching1,362,573 (42.0)680 (35.7)
       Urban teaching1,494,352 (46.5)1,033 (55.1)
      Control/ownership of hospital6.36*
       Government, non-federal (public)458,367 (13.9)283 (14.7)
       Private, not-for-profit (voluntary)2,343,123 (72.9)1,435 (76.4)
       Private, investor-owned (proprietary)420,279 (13.3)167 (8.9)
      Median household income for patient’s ZIP code2.01
       1st quartile: $1–$38,999856,850 (26.8)552 (29.6)
       2nd quartile: $39,000–$47,999815,225 (25.5)449 (24.1)
       3rd quartile: $48,000–$62,999802,771 (25.0)473 (25.1)
       4th quartile: ≥$63,000729,487 (22.7)398 (21.3)
      Age (in years), M (SE)27.6 (0.07)28.5 (0.16)27.18***
      Note: Percentages are weighted; significant differences are presented for weighted sample. Boldface indicates statistical significance (*p<0.05; **p<0.01; ***p<0.001).
      a Comorbidity variable is generated using the AHRQ comorbidity software.

      McCarthy J. Deaf people and social security. http://libguides.gallaudet.edu/content.php?pid=119476&sid=4748939. Published March 2014. Accessed June 3, 2015.

      Patients are considered to have comorbidity if their discharge records show that they have one more of the 29 types of patient comorbidities identified by AHRQ using standard methods by Elixhauser.
      • Iezzoni L.I.
      • O’Day B.L.
      • Killeen M.
      • Harker H.
      Communicating about health care: observations from persons who are deaf or hard of hearing.
      AHRQ, Agency for Healthcare Research and Quality; HCUP, Healthcare Cost and Utilization Project; HL, hearing loss; NIS, nationwide inpatient sample.
      Table 3 reports the unadjusted, weighted comparison in adverse birth outcomes between women with and without HL. Women with HL had higher rates of both preterm birth and low birth weight compared with other women. After controlling for model covariates, women with HL were significantly more likely to have both preterm birth (OR=1.28, 95% CI=1.08, 1.52, p<0.001) and low birth weight (OR=1.43, 95% CI=1.09, 1.90, p<0.05) (Table 4).
      Table 3Unadjusted, Weighted Birth Outcomes for Women With and Without Hearing Loss, NIS, HCUP, 2008–2011
      OutcomesWomen without HL, n (%) (n=3,264,675)Women with HL, n (%) (n=1,902)Test statistics (F test)
      Birth outcomes
       Preterm birth233,974 (7.20)189 (9.97)19.71***
       Low birth weight71,289 (2.18)60 (3.13)7.54***
      Note: Percentages are weighted; significant differences are presented for weighted sample. Boldface indicates statistical significance (*p<0.05; **p<0.01; ***p<0.001).
      HCUP, Healthcare Cost and Utilization Project; HL, hearing loss; NIS, Nationwide Inpatient Sample.
      Table 4Logistic Regression Analysis for Hearing Loss Status and Other Relevant Variables Predicting Birth Outcomes—U.S.
      VariablesPreterm birth, OR (95% CI) (n=2,708,127)Low birth weight, OR (95% CI) (n=2,708,127)
      Hearing status
       Women without HL (ref)1 (1)1 (1)
       Women with HL1.28** (1.08, 1.52)1.43* (1.09, 1.90)
      Age (in years)
       <241 (1)1 (1)
       25–340.96*** (0.95, 0.97)0.74*** (0.72, 0.76)
       >341.15*** (1.13, 1.18)0.81*** (0.78, 0.84)
      Race and ethnicity
       Non-Hispanic white (ref)1 (1)1 (1)
       Non-Hispanic black1.31*** (1.26, 1.37)1.27*** (1.20, 1.34)
       Hispanic0.91*** (0.86, 0.97)0.65*** (0.60, 0.71)
       Non-Hispanic other0.97 (0.93, 1.02)1.10*** (1.04, 1.17)
      Type of insurance coverage
       Private insurance (ref)1 (1)1 (1)
       Public insurance1.12*** (1.09, 1.14)1.09** (1.04, 1.13)
       Uninsured1.18*** (1.11, 1.26)0.96 (0.88, 1.04)
      Comorbidity
      Comorbidity variable is generated using the AHRQ comorbidity software.64 Patients are considered to have comorbidity if their discharge records show that they have one more of the 29 types of patient comorbidities identified by AHRQ using standard methods by Elixhauser.38 AHRQ, Agency for Healthcare Research and Quality; HCUP, Healthcare Cost and Utilization Project; HL, hearing loss.
       No comorbidity1 (1)1 (1)
       One or more comorbidities1.58*** (1.53, 1.63)1.40*** (1.35, 1.46)
      Region of hospital
       Northeast (ref)1 (1)1 (1)
       Midwest1.02 (0.94, 1.11)0.99 (0.88, 1.11)
       South1.18*** (1.09, 1.28)1.11 (0.99, 1.25)
       West1.15*** (1.06, 1.25)0.99 (0.88, 1.12)
      Hospital location and teaching status
       Urban teaching (ref)1 (1)1 (1)
       Rural0.61*** (0.55, 0.67)0.76*** (0.67, 0.85)
       Urban non-teaching0.74*** (0.69, 0.79)0.83*** (0.76, 0.91)
      Ownership of hospital
       Private (ref)1 (1)1 (1)
       Public1.05 (0.93, 1.19)0.95 (0.79, 1.14)
      Median household income for patient’s ZIP code
       4th quartile: ≥$63,000 (ref)1 (1)1 (1)
       1st quartile: $1–$38,9991.17*** (1.11, 1.22)0.99 (0.91, 1.07)
       2nd quartile: $39,000–$47,9991.08*** (1.04, 1.12)1.01 (0.95, 1.09)
       3rd quartile: $48,000–$62,9991.03 (1.00, 1.06)0.98 (0.93, 1.04)
      Year
       Calendar year=2008 (ref)1 (1)1 (1)
       Calendar year=20090.94 (0.88, 1.00)0.99 (0.91, 1.08)
       Calendar year=20100.98 (0.92, 1.04)1.21*** (1.11, 1.33)
       Calendar year=20110.88*** (0.82, 0.93)1.20*** (1.10, 1.31)
      Source: HCUP 2008–2011.
      Note: Boldface indicates statistical significance (*p<0.05; **p<0.01; ***p<0.001).
      a Comorbidity variable is generated using the AHRQ comorbidity software.

      McCarthy J. Deaf people and social security. http://libguides.gallaudet.edu/content.php?pid=119476&sid=4748939. Published March 2014. Accessed June 3, 2015.

      Patients are considered to have comorbidity if their discharge records show that they have one more of the 29 types of patient comorbidities identified by AHRQ using standard methods by Elixhauser.
      • Iezzoni L.I.
      • O’Day B.L.
      • Killeen M.
      • Harker H.
      Communicating about health care: observations from persons who are deaf or hard of hearing.
      AHRQ, Agency for Healthcare Research and Quality; HCUP, Healthcare Cost and Utilization Project; HL, hearing loss.

      Discussion

      To the investigators’ knowledge, this is the first population-based examination of birth outcomes among U.S. women with HL. This study demonstrates that HL is associated with elevated risk of selected adverse birth outcomes. Controlling for socioeconomic and demographic characteristics and comorbidity, HL is significantly associated with preterm delivery and low birth weight infants. Although measuring the impact of the poor birth outcomes among women with HL is beyond the scope of this study, prematurity is generally associated with significant long-term consequences for the infant as well as significant costs to the family and society.
      • Hobel C.J.
      • Goldstein A.
      • Barrett E.S.
      Psychosocial stress and pregnancy outcome.
      • Goldenberg R.L.
      • Culhane J.F.
      • Iams J.D.
      • Romero R.
      Epidemiology and causes of preterm birth.
      • Illsley R.
      • Mitchell R.
      Low Birth Weight: A Medical, Psychological, and Social Study.
      The findings of this study call for a systematic examination of the pregnancy experiences, complications, costs, quality of care, and outcomes of women with HL. In addition, given the results of this study, further research is warranted in understanding these disparities in birth outcomes between women with and without HL.
      Given the cross-sectional nature of this study, it is difficult to ascertain the causal factors associated with poor birth outcomes among women with HL. There are several potential factors that may contribute to the study findings. First, HL represents a significant source of communication barrier in the healthcare setting.
      • McKee M.M.
      • Moreland C.
      • Atcherson S.R.
      • Zazove P.
      Hearing loss: communicating with the patient who is deaf or hard of hearing.
      • Bainbridge K.E.
      • Wallhagen M.I.
      Hearing loss in an aging American population: extent, impact, and management.
      Poor health communication adversely affects a variety of health-related outcomes, especially health behaviors, treatment adherence, and patient satisfaction.
      • DeWalt D.A.
      • Boone R.S.
      • Pignone M.P.
      Literacy and its relationship with self-efficacy, trust, and participation in medical decision making.
      • Stewart M.A.
      Effective physician-patient communication and health outcomes: a review.
      • McKee M.M.
      • Winters P.C.
      • Fiscella K.
      Low education as a risk factor for undiagnosed angina.
      • Torres R.E.
      The pervading role of language on health.
      • Barnett D.D.
      • Koul R.
      • Coppola N.M.
      Satisfaction with health care among people with hearing impairment: a survey of Medicare beneficiaries.
      A 2006 qualitative study found that Deaf women were less satisfied with their patient–provider communication and prenatal care than hearing women. Deaf women were also more likely to have shorter breastfeeding duration if they did not have language access through interpreters and sign language–using providers, and access to technologies.
      • Chin N.P.
      • Cuculick J.
      • Starr M.
      • Panko T.
      • Widanka H.
      • Dozier A.
      Deaf mothers and breastfeeding: do unique features of deaf culture and language support breastfeeding success?.
      Effective communication between healthcare providers and patients during the prenatal period is especially critical. Prenatal counseling is largely focused on patient education, including encouraging healthy behaviors and reducing risk factors to improve the chances of an optimal pregnancy outcome.
      Second, sexual health knowledge among individuals with HL is lower than what is seen in the general population.
      • Heuttel K.L.
      • Rothstein W.G.
      HIV/AIDS knowledge and information sources among deaf and hearing college students.
      • Peinkofer J.R.
      HIV education for the deaf, a vulnerable minority.
      • Wollin J.
      • Elder R.
      Mammograms and Pap smears for Australian deaf women.
      • Woodroffe T.
      • Gorenflo D.W.
      • Meador H.E.
      • Zazove P.
      Knowledge and attitudes about AIDS among deaf and hard of hearing persons.
      • Tamaskar P.
      • Malia T.
      • Stern C.
      • Gorenflo D.
      • Meador H.
      • Zazove P.
      Preventive attitudes and beliefs of deaf and hard-of-hearing individuals.
      • Heiman E.
      • Haynes S.
      • McKee M.
      Sexual health behaviors of Deaf American Sign Language (ASL) users.
      It is less clear if pregnancy-related knowledge is also reduced among women with HL. Individuals with HL struggle with inadequate health literacy and access to health information, including incidental learning opportunities.
      • McKee M.M.
      • Paasche-Orlow M.K.
      • Winters P.C.
      • et al.
      Assessing health literacy in deaf American Sign Language users.
      Though health literacy has been demonstrated to correlate with health knowledge in other studies, no known studies have examined how this may affect women’s health, especially prenatal and perinatal health. Lower health knowledge and inadequate health literacy are associated with poorer health access, delayed medical care seeking, higher mistrust of the healthcare system, and poorer health outcomes, and may be a potential source of higher rates of adverse birth outcomes among women with HL.
      • Paasche-Orlow M.K.
      • Wolf M.S.
      The causal pathways linking health literacy to health outcomes.
      In addition, women with HL represent a vulnerable population. This is a population that struggles with a rate of interpersonal violence nearly double that of the general population.
      • Pollard R.Q.
      • Sutter E.
      • Cerulli C.
      Intimate partner violence reported by two samples of deaf adults via a computerized American Sign Language Survey.
      • Anderson M.L.
      • Kobek Pezzarossi C.M.
      Violence against deaf women: effect of partner hearing status.
      Studies demonstrate that women are at high risk for interpersonal violence during their pregnancy.
      • Gazmararian J.A.
      • Lazorick S.
      • Spitz A.M.
      • Ballard T.J.
      • Saltzman L.E.
      • Marks J.S.
      Prevalence of violence against pregnant women.
      Women who have experienced interpersonal violence victimization have higher rates of sexually transmitted infections and poorer pregnancy-related outcomes, including low birth weight and preterm babies.
      • Campbell J.
      • Torres S.
      • Ryan J.
      • et al.
      Physical and nonphysical partner abuse and other risk factors for low birth weight among full term and preterm babies: a multiethnic case-control study.
      Psychosocial stress is reported higher among women with disabilities
      • Mitra M.
      • Long-Bellil L.M.
      • Smeltzer S.C.
      • Iezzoni L.I.
      A perinatal health framework for women with physical disabilities.
      than the general population. This is a potential concern given the role of psychosocial stress on adverse pregnancy outcomes, including low birth weights and preterm deliveries.
      • Hobel C.J.
      • Goldstein A.
      • Barrett E.S.
      Psychosocial stress and pregnancy outcome.
      Additionally, women with HL are more likely to have public insurance, including Medicare. This is not a surprising finding. Blanchfield and colleagues
      • Blanchfield B.B.
      • Feldman J.J.
      • Dunbar J.L.
      • Gardner E.N.
      The severely to profoundly hearing-impaired population in the United States: prevalence estimates and demographics.
      analyzed data from multiple national data sets and found that individuals with HL were significantly more likely to be publicly insured. Individuals with HL can qualify for both the Medicare and Social Security Disability Insurance on the basis of their hearing disability, especially if their disability prevents successful employment.

      McCarthy J. Deaf people and social security. http://libguides.gallaudet.edu/content.php?pid=119476&sid=4748939. Published March 2014. Accessed June 3, 2015.

      There may be additional biological factors that may explain some of the perinatal outcomes among women with HL. Genetic factors are increasingly recognized as important determinants of preterm delivery, but the magnitude of effect and the degree to which they contribute to differences in preterm risk across populations remain largely unknown.
      • Beck S.
      • Wojdyla D.
      • Say L.
      • et al.
      The worldwide incidence of preterm birth: a systematic review of maternal mortality and morbidity.
      This is relevant given that the majority of congenital HL is likely due to genetic polymorphisms, with the majority due to autosomal recessive HL,
      • Zazove P.
      • Atcherson S.R.
      • Moreland C.
      • McKee M.M.
      Hearing loss: diagnosis and evaluation.
      • Smith R.J.H.
      • Shearer A.E.
      • Hildebrand M.S.
      • Van Camp G.
      Deafness and hereditary hearing loss overview.
      yet little is known about how these are phenotypically expressed and if any obstetric and fetal risk factors are associated with them.
      Given these prior studies, and the findings from this study, longitudinal studies are needed to examine the pathways through which women with HL experience poor birth outcomes. A recent perinatal health framework developed by Mitra et al.
      • Mitra M.
      • Long-Bellil L.M.
      • Smeltzer S.C.
      • Iezzoni L.I.
      A perinatal health framework for women with physical disabilities.
      identified a set of individual and mediating factors that may impact maternal and birth outcomes for women with physical disabilities. Mediating factors, for example, include provider knowledge and attitudes toward pregnancy, family support, and psychosocial factors such as stressful life events. Although these factors are not identifiable in the HCUP data, this framework may be also applicable to women with HL. Given the earlier studies on patient–provider communication, potential biological factors, interpersonal violence, and health knowledge and health literacy among people with HL and the general dissatisfaction of people with HL with their health care, these mediating factors could potentially explain the poor birth outcomes found in this study.

      Limitations

      The study limitations warrant consideration. First, some NIS data may have been miscoded. Second, the unit of analysis was hospitalization rather than the individual patient; therefore, any woman who delivered more than once in a single calendar year was counted twice. However, this situation is not likely to be common because short interpregnancy intervals resulting in U.S. women giving birth within one 12-month period are rare;
      • Adams M.M.
      • Delaney K.M.
      • Stupp P.W.
      • McCarthy B.J.
      • Rawlings J.S.
      The relationship of interpregnancy interval to infant birthweight and length of gestation among low-risk women, Georgia.
      thus, few women give birth twice in 1 calendar year. Further, this unit of analysis precludes identification of complications that were treated in the hospital prior to delivery. Third, the estimates are conservatively biased because some women with HL were probably not assigned the ICD-9 code for their HL.
      • Halpin C.F.
      • Iezzoni L.I.
      • Rauch S.
      Medical record documentation of patients’ hearing loss by physicians.
      Therefore, the weighted estimate of 10,462 deliveries for the 2008–2011 period occurring to women with HL should not be interpreted as an incidence statistic. Yet, the smaller-than-anticipated number may be reflective of not-well-understood providers’ coding behaviors. For example, healthcare providers may only be prompted to add ICD-9 HL codes when the HL resulted in significant communication barriers during the hospital visit. Undercoding and underdiagnosis of HL is a common issue across different types of healthcare visits.
      • Wallhagen M.I.
      • Pettengill E.
      Hearing impairment: significant but underassessed in primary care settings.
      Patients may be reluctant to disclose their HL owing to fear of discrimination, perceptions of disability, and vanity.
      • Wallhagen M.I.
      The stigma of hearing loss.
      These factors likely resulted in low rates of ICD-9 codes for HL. Fourth, the level of detail provided by the NIS was limited; future research could explore the relationships between early prenatal care and pregnancy and health outcomes. Fifth, these data do not permit longitudinal analyses, which could facilitate understanding the health outcomes of women and their children over time. Sixth, the NIS does not permit linkage between the hospital records of the infant and the mother, so it was not possible to analyze infant outcomes other than those reported here (which are part of the maternal discharge summary). Additionally, household income included in this paper is based on the median household income for mother’s ZIP code. Patient-level household income data are not included in the NIS. Additionally, owing to HCUP data restrictions, the study was unable to account for marital status, a potent variable that has unique impacts on both low birth weight and preterm birth.
      • Shah P.S.
      • Zao J.
      • Ali S.
      Maternal marital status and birth outcomes: a systematic review and meta-analyses.
      Another potential limitation is out-of-hospital deliveries. Although recent studies
      • MacDorman M.F.
      • Declercq E.
      • Mathews T.J.
      Recent trends in out-of-hospital births in the United States.
      • MacDorman M.F.
      • Mathews T.J.
      • Declercq E.
      Home births in the United States, 1990-2009.
      • MacDorman M.F.
      • Declercq E.
      Trends and characteristics of United States out-of-hospital births 2004–2014: new information on risk status and access to care.
      have shown an increase in the trend of out-of-hospital deliveries, only 1.5% of all deliveries in the U.S. occurred out of hospital. Notably, women who have lower birth risks and fewer or no comorbidities are among those who have given birth outside hospitals. Though there are no exact statistics on out-of-hospital deliveries among women with HL, the investigators believe that given higher comorbidity rates among women with HL, the rate of out-of-hospital deliveries among women with HL would be lower than those of the general obstetric population. Finally, missing data of the race variable was another limitation. In the combined 2008–2011 HCUP data set, values for about 13% of the race variable were missing. Most of the data were missing for the early cross-section years of the 2008–2011 HCUP data set, including 20% in 2008, 15% in 2009, 11% in 2010, and 9% in 2011. Missing values for race were considered missing at random and analyses were performed using observations that did not contain missing data for the race variable. Additionally, the study tested the regression results with the full sample by excluding the race variable from the model and did not find significant bias in the ORs.
      This study has important strengths. The NIS provides high-quality, nationally representative data and therefore permits this study to draw inferences about the entire U.S. population of women with HL who have given birth. Despite potential omitted variable bias, the sample is less constrained by selection bias or sampling bias arising from convenience samples derived from a single hospital, service provider organization, or single geographic region.

      Conclusions

      This study provides a first examination of birth outcomes among U.S. women with HL. Results highlight the need for further research using longitudinal data and direct measures of HL to understand the causes of disparities in birth outcomes, and to examine the perinatal care experiences and potential barriers to perinatal care experienced by women with HL. Efforts to develop clinical interventions and maternal and child health programs are also needed to improve these adverse outcomes among women with HL.

      Acknowledgments

      Support for this study was provided by the Lurie Institute for Disability Policy at the Heller School for Social Policy and Management at Brandeis University and by the National Institute on Disability, Independent Living, and Rehabilitation Research’s Advanced Rehabilitation Research Training Program on Health and Functioning of People with Disabilities, grant # 90AR5024-01-00.
      Dr. Mitra takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design by Mitra and McKee. Drafting and revision of manuscript by Mitra, McKee, Akobirshoev, Iezzoni. Statistical analysis by Akobirshoev.
      No financial disclosures were reported by the authors of this paper.

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