Abstract
Background
Growing numbers of reproductive-age U.S. women with chronic physical disabilities (CPD) raise questions about their pregnancy experiences. Little is known about the health risks of women with versus without CPD by current pregnancy status.
Methods
We analyzed cross-sectional, nationally-representative National Health Interview Survey data from 2006–2011, which includes 47,629 civilian, noninstitutionalized women ages 18–49. NHIS asks about specified movement difficulties, current pregnancy, and various health and health risk indicators, including tobacco use and body mass index (BMI). We used responses from 8 movement difficulty and other questions to identify women with mobility difficulties caused by chronic physical health conditions.
Findings
Across all women regardless of CPD, women reporting current pregnancy are significantly less likely to currently smoke tobacco and report certain mental health problems. Among currently pregnant women only, women with CPD are more likely to smoke cigarettes every day (12.2%) versus 6.3% for pregnant women without CPD (p ≤ 0.001). Among currently pregnant women, 17.7% of women with CPD have BMIs in the non-overweight range, compared with 40.1% of women without CPD (p ≤ 0.0001). Currently pregnant women with CPD are significantly more likely to report having any mental health problems, 66.6% compared with 29.7% among women without CPD (p ≤ 0.0001).
Conclusions
For all women, currently pregnant women appear to have fewer health risks and mental health concerns than nonpregnant women. Among pregnant women, women with CPD have higher rates than other women of health risk factors that could affect maternal and infant outcomes.
Keywords: disability, pregnancy, health risks, mental health, National Health Interview Survey
Introduction and Background
Persons with chronic physical disabilities (CPD) – defined here as functional impairments of upper or lower extremities that limit mobility – report worse overall physical and mental health and higher rates of health risk factors, such as tobacco use and obesity, than do individuals without disabilities.(1) In particular, women with CPD report higher rates of mental health problems and fair or poor general health than do other women.(2–5) Women with disabilities are also more likely than other women to report tobacco use and body excess weight.(2, 6, 7)
Little is known, however, about the health and health risk factors of women with CPD who are pregnant and how these attributes compare with those of currently pregnant nondisabled women. Women with CPD, regardless of pregnancy status, generally have higher rates of risk factors strongly associated with adverse pregnancy outcomes. For example, women with CPD have relatively higher rates of cigarette smoking, an exposure linked to increased risks of preterm births, low infant birth weight, and infant mortality.(8–13) Using data from Massachusetts Pregnancy Risk Assessment Monitoring System (PRAMS) surveys, Mitra and colleagues found that 25.2% of women with self-reported disabilities, broadly defined, smoked during the last trimester of pregnancy, compared with 9.4% of other women.(14) Smoking prevalence around pregnancy varies substantially across states,(8) however, and whether these Massachusetts smoking findings generalize nationwide is unclear.
Obesity, which is more prevalent among women with CPD regardless of pregnancy, also increases risks of poor outcomes when women become pregnant. Studies, albeit many from outside the U.S. (with different dietary patterns), indicate that pre-pregnancy obesity is associated with higher rates of stillbirth, neonatal death, and neonatal intensive care admissions.(15–22) Furthermore, pre-pregnancy obesity is associated with large-forgestational-age infants, increasing likelihood of Caesarean deliveries and childhood obesity, which has negative long-term consequences. Additionally, mental health problems, which are often more common among women with disabilities, can complicate pregnancy experiences. For instance, depression during pregnancy has been strongly linked to development of postpartum depression.(23, 24)
In future decades, the numbers of women with CPD of reproductive age will rise,(25) which will also likely increase numbers of pregnancies involving women with CPD. Therefore, learning more about health conditions and risk factors that might affect obstetrical needs and outcomes of women with CPD is important. Few data sets contain information on CPD, current pregnancy, and potential health risk factors. The federal, cross-sectional National Health Interview Survey (NHIS) includes a single question about self-reported “current” pregnancy; it also contains relatively detailed information on mobility-related functional limitations and self-reported indicators of physical and mental health and health risk factors. NHIS therefore offers a useful data set for preliminary explorations of current pregnancy, disability, and health risk factors.
The findings reported here are part of a larger study, in which we have examined sociodemographic characteristics associated with current pregnancy for women with CPD, underlying causes of disability associated with current pregnancy, and the presence of comorbid health conditions associated with CPD and current pregnancy (26–28). Here, we also use these NHIS data to address three new research questions:
What is the prevalence of selected, self-reported health risk factors and mental health problems for U.S. women with and without CPD?
What is the prevalence of these self-reported health risk factors and mental health problems by CPD status and by current pregnancy?
What are the associations of CPD and current pregnancy with these self-reported health risk factors and mental health problems?
These cross-sectional data are descriptive and our analyses therefore necessarily represent only associations rather than causal linkages. Nonetheless, these findings provide important preliminary evidence for anticipating the potential clinical needs of pregnant women with CPD and suggest how these needs might differ from those of pregnant women without CPD.
Methods
Data
We used freely available, 2006–2011 NHIS Public Release data from the National Center for Health Statistics (NCHS, http://www.cdc.gov/nchs/nhis/nhis_questionnaires.htm). NHIS surveys U.S. civilian, noninstitutionalized, community residents, and it oversamples black, Hispanic, and Asian populations. U.S. Census Bureau interviewers trained by NCHS staff gather the NHIS data during face-to-face interviews in respondents' homes. All members of sampled households ages 17 and older who are home during the interview are invited to respond for themselves.
The NHIS Basic Module contains 3 components: Family Core, Sample Adult Core, and Sample Child Core. The Family Core collects information on all family members. Within each family, one randomly selected adult (age ≥ 18) receives the Sample Adult Core survey, which asks detailed health, health behavior, and functional status questions. A knowledgeable adult family member provides proxy responses for sampled adults who are physically or mentally unable to respond. The 2011 NHIS Sample Adult Core, for example, included 33,014 individuals; 465 had proxy responses; the conditional response rate for the Sample Adult Core was 81.6%.(29) We drew our study population from the 157,351 total participants in the 2006–2011 Sample Adult Core surveys, which had similar numbers of participants and response rates. By applying NHIS sampling weights, our analyses produce nationally representative figures.
The Sample Adult Core asks women ages 18–49 whether they are “currently pregnant.” We initially selected the 47,886 women ages 18–49 in the data set and then eliminated women with: missing responses to the pregnancy question (0.2%); no responses to any of the 8 functional status questions for determining CPD (0.3%); and 7 women who reported Alzheimer's disease.(27) Our final sample included 47,629 women, with 263 (0.6%) proxy respondents.
Chronic Physical Disability Indicator
To identify CPD, we started with NCHS's “movement difficulty severity” algorithm,(1) which uses responses to questions about difficulties caused by health problems with: walking a quarter mile; walking up 10 steps without resting; standing for about 2 hours; sitting for about 2 hours; stooping, bending, or kneeling; reaching up overhead; using fingers to grasp or handle small objects; and lifting or carrying something as heavy at 10 pounds.(26) The question stem asks respondents not to report difficulties caused by pregnancy. NCHS's algorithm considers only responses indicating “somewhat difficult” or worse difficulties. Each activity receives a weight representing its presumed importance for maintaining independent lifestyles. The movement difficulty algorithm has 5 severity levels (1 to 5, from least to most severe).
We refined our CPD indicator in the following three steps, as described in detail elsewhere.(26) First, despite instructions not to report pregnancy-related difficulties, 138 (2.0%) women indicated in later questions that pregnancy produced their impairments; we dropped these cases from the CPD group. Second, we eliminated women (4.1%) who reported that their movement difficulties were caused by conditions other than physical health problems (e.g., intellectual disabilities, psychiatric or mental health problems, substance abuse). Finally, we removed women (4.8%) who described their underlying health problem as not “chronic.” After these deletions, our final sample included 6,043 women (12.7%) with CPD. Because of small numbers with the highest severity level impairments, we combined cases across levels 3–5.(26)
Health, Mental Health, and Heath Risk Factor Indicators
The Family Core questionnaire asks about “health in general” for each family member, while the Sample Adult Core asks whether this health is better, worse, or about the same as it was one year previously. In the “Adult Conditions” section, the Sample Adult Core asks a series of questions relating to mental health. In addition, respondents are asked a series of questions labeled “Adult Health Behaviors,” which include queries about tobacco use, leisure time physical activities, sleep, and height and weight.
Height and weight are used to calculated body mass index (BMI, weight(kg)/(height(m)2), which is included in the NHIS Public Release files. However, the weight question asks only for weight “without shoes” – not for pre-pregnancy weight for women who are currently pregnant. BMIs typically rise, especially in late pregnancy, as an artifact of pregnancy-related weight gains. Although obstetrical researchers do calculate BMIs among pregnant women for certain studies of pregnancy outcomes, BMIs must be interpreted cautiously when comparing pregnant with nonpregnant women. As described below, for certain analyses, we therefore focus only on women reporting current pregnancy, comparing those with and without CPD. Since all women in these analyses are pregnant, these BMI comparisons should not be biased by BMI pregnancy artifact.
After questions about functional difficulties, the Sample Adult Core asks respondents about condition(s) that caused their difficulties. Respondents can report more than one condition. As noted above, we eliminated from our CPD group women who listed only causes that are not physical health problems.(26) Women could also list mental health conditions as causing their functional difficulties. We identified those women with CPD who, in addition to physical health causes, also cited mental health causes that they reported as chronic.
Other Variable Definitions
To describe the study population and conduct multivariable analyses, we used basic sociodemographic characteristics from the Sample Adult Core, except for family poverty from the Family Core.
We considered adding a covariate to models identifying proxy responses. Sample Adult Core respondents may require a proxy for various reasons, including not only physical, behavioral, or cognitive inability to respond but also not being at home when the NHIS interviewer arrives (e.g., because of working). Among the 263 women in our sample with proxy responses, 27.8% have CPD and 72.2% do not. Across these 263 women, 3.8% report being currently pregnant, the same percentage as women without CPD in the whole sample. However, none of the 73 proxied respondents with CPD reports being currently pregnant. Thus, the proxies as a group look more like women without CPD in terms of pregnancy percentages than women with CPD. With 0 pregnancies in the CPD group with proxy responses, we were unable to add a proxy variable to multivariable regression analyses.
Analysis
All analyses used SAS Version 9.2 (Cary, NC) and employed NHIS sampling weights to produce nationally-representative figures, including percentages. Because of strong relationships between age and disability level and between age and pregnancy,(26) we used direct standardization to adjust certain demographic characteristics by age category (Table 1). We used X2 tests to assess bivariable associations. We performed multivariable logistic regressions in separate models to predict five health conditions and risk factors indicated as binary (yes/no) outcomes as follows: fair or poor overall health; current smoker; obese (BMI ≥ 30); performs vigorous leisure time physical activity; and any mental health problem. The multivariable logistic regressions controlled for: age category (18–24, 25–29, 30–34, 35–39, 40–44, 45–49); race (white only, black only, Asian only, other race and multiple races); ethnicity (Hispanic, not Hispanic); education (less than high school, high school graduate, some college or associate's degree, college degree and higher education); and household income below federal poverty level. In addition to these core sociodemographic variables, in three separate sets of regressions, we added: (1) CPD only; (2) pregnancy only; and (3) CPD and pregnancy. We report adjusted odd ratios (AORs) and 95% confidence intervals from these analyses.
Table 1.
Characteristics | All women | Women without CPD | Women with CPD | Severity of CPD | ||
---|---|---|---|---|---|---|
1 | 2 | 3–5 | ||||
Sample size: number of respondents | 47,629 | 41,586 | 6,043 | 2,084 | 1,711 | 2,248 |
% of total sample in column | 100.0% | 87.3% | 12.7% | 4.4% | 3.6% | 4.7% |
Age in years: mean (SD) | 33.8 (0.1) | 33.2 (0.1) | 38.1 (0.2)* | 36.2 (0.3) | 38.1 (0.3)* | 39.9 (0.2)* |
Age category: % | ||||||
18–24 | 21.6% | 23.1% | 10.9%* | 16.0% | 11.1%* | 5.7%* |
25–29 | 15.4 | 16.3 | 9.2 | 12.6 | 8.8 | 6.1 |
30–34 | 14.7 | 15.2 | 11.4 | 11.7 | 11.4 | 11.1 |
35–39 | 15.0 | 14.9 | 15.7 | 15.3 | 14.4 | 17.2 |
40–44 | 16.2 | 15.4 | 21.9 | 18.9 | 24.3 | 23.0 |
45–49 | 17.1 | 15.1 | 30.9 | 25.7 | 30.0 | 36.9 |
Race: %a | ||||||
White only | 77.5% | 77.5% | 77.5%* | 81.3% | 76.7%§ | 74.2%* |
Black only | 14.3 | 13.9 | 16.6 | 13.0 | 16.6 | 20.4 |
Asian only | 5.4 | 5.9 | 2.1 | 2.2 | 2.6 | 1.5 |
Other race including multiple | 2.8 | 2.7 | 3.8 | 3.5 | 4.1 | 3.9 |
Ethnicity: %a | ||||||
Hispanic | 16.3% | 16.7% | 13.0%* | 14.0% | 12.6% | 12.4%# |
Not Hispanic | 83.7 | 83.3 | 87.0 | 86.0 | 87.4 | 87.6 |
Marital status:b %a | ||||||
Single, never married | 28.4% | 29.2% | 22.7%* | 24.2% | 23.1%+ | 20.9%* |
Married/living with partner | 60.6 | 60.8 | 58.8 | 62.0 | 58.8 | 55.8 |
Divorced/separated | 10.2 | 9.2 | 17.0 | 13.1 | 16.9 | 20.8 |
Education:b %a | ||||||
Less than high school | 12.6% | 11.8% | 18.5%* | 13.2% | 18.6%* | 23.7%* |
High school | 23.9 | 23.0 | 30.0 | 26.9 | 30.0 | 33.0 |
Some college, associate degree | 34.4 | 34.1 | 36.0 | 37.2 | 37.0 | 34.1 |
College, more than college degree | 28.5 | 30.5 | 14.8 | 22.4 | 14.0 | 7.9 |
Family income < poverty threshold: %a | 15.1% | 13.9% | 23.8%* | 15.2% | 23.1%* | 33.1%* |
Currently pregnant: adjusted %# | 3.5% | 3.8% | 2.0%* | 2.6% | 1.8%# | 1.5%+ |
Health in general:" %a | ||||||
Excellent | 34.4% | 37.9% | 9.7%* | 16.6% | 9.6%* | 3.0%* |
Very good | 33.6 | 35.4 | 21.1 | 34.7 | 19.5 | 8.7 |
Good | 23.7 | 22.2 | 34.1 | 35.6 | 40.4 | 27.6 |
Fair | 6.8 | 4.2 | 24.9 | 11.2 | 25.3 | 38.4 |
Poor | 1.6 | 0.4 | 10.1 | 1.8 | 5.1 | 22.3 |
Compared with 12 months ago, health is: %b | ||||||
Better | 20.6% | 20.6% | 20.7%* | 26.4% | 22.3%* | 13.6%* |
Worse | 7.4 | 4.8 | 26.0 | 14.7 | 21.8 | 40.5 |
About the same | 71.9 | 74.6 | 53.2 | 58.9 | 55.7 | 45.6 |
Body mass index: mean (SD) | 30.4 (0.1) | 29.8 (0.1) | 34.5 (0.3)* | 33.3 (0.5) | 34.5 (0.5) | 35.6 (0.5)* |
Hours spent sleeping each day: mean (SD) | 8.0 (0.1) | 8.1 (0.1) | 7.8 (0.1)# | 7.4 (0.1) | 7.4 (0.2) | 8.5 (0.3)§ |
p values for comparisons of women with and without chronic physical disability (CPD) and for women with CPD severity level 2 versus level 1 and levels 3–5 versus level 1
p ≤ 0.0001
p ≤ 0.001
p ≤ 0.01
p ≤ 0.05
Weighted percents adjusted by age category
Other and missing responses not shown
Results
Demographic Characteristics, Current Pregnancy, and General Health
Table 1 shows basic demographic characteristics, current pregnancy status, and self-reports of general health of U.S. women ages 18–49 with and without CPD. Women with CPD are significantly older than women without CPD, and they are significantly more likely to be black, non-Hispanic, divorced or separated, less educated, and have family incomes under the federal poverty threshold. As CPD severity increases, similar trends appear: for example, with rising severity, women are progressively older, black, less educated, and impoverished.
Current pregnancy rates across all women are 3.5% (Table 1). While 3.8% of women without CPD report current pregnancy, only 2.0% of women with CPD are currently pregnant. Current pregnancy rates fall significantly and monotonically as CPD severity rises.
Table 1 also shows self-reported general health, a comparison with health one year previously, BMI, and hours spent sleeping each day. Compared with women without CPD, women with CPD are significantly more likely to report fair or poor general health, and these percentages increase with rising CPD severity. Women with CPD are also significantly more likely to report worse health than last year, again with monotonically rising percentages by CPD severity. Mean BMI values are significantly higher for women with CPD, with average BMIs rising with worsening CPD severity. Finally, women with CPD sleep significantly less each day than other women, although the absolute value of this difference (0.3 hours) is small.
Health Risks and Mental Health Problems by CPD and Current Pregnancy
Table 2 shows percentages of various subgroups of women – categorized by current pregnancy and by CPD – by cigarette smoking history, BMI category, and vigorous and light or moderate leisure time physical activity. Across all women regardless of CPD, those who report current pregnancy are significantly less likely to currently smoke tobacco; currently pregnant women are, not surprisingly given the BMI pregnancy artifact, significantly less likely to have healthy BMIs; and significantly less likely to engage in any leisure time activity.
Table 2.
Health risks | All women | Pregnant women only | Non-pregnant women only | Women with CPD by severity | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3–5 | ||||||||||
Pregnant | CPD | CPD | Pregnant | Pregnant | Pregnant | |||||||
Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | |
Sample size: total number | 1,685 | 45,944 | 128 | 1,557 | 5,915 | 40,029 | 62 | 2,022 | 34 | 1,677 | 32 | 2,216 |
% of total sample in yes/no columns | 3.5% | 96.5% | 7.6% | 92.4% | 12.9% | 87.1% | 2.6% | 97.4% | 1.8% | 98.2% | 1.5% | 98.5% |
Cigarette smoking: column %a | ||||||||||||
Current every day smoker | 6.7% | 16.3%* | 12.2% | 6.3%+ | 31.1% | 14.2%* | 5.1% | 25.0%§ | 22.7% | 31.8% | 15.1% | 36.7% |
Current some day smoker | 3.2 | 4.3 | 3.5 | 3.2 | 5.1 | 4.2 | 2.8 | 4.7 | 8.8 | 4.5 | 0 | 5.8 |
Former smoker | 19.0 | 12.3 | 28.7 | 18.3 | 15.1 | 11.9 | 27.8 | 15.2 | 22.7 | 14.2 | 35.7 | 15.6 |
Never smoked | 70.5 | 66.7 | 55.6 | 71.6 | 48.4 | 69.4 | 64.3 | 54.9 | 45.8 | 49.3 | 49.2 | 41.4 |
Body mass index: column % | ||||||||||||
Underweight (< 18.5) | 0.9% | 2.7%* | 1.4% | 0.8%* | 1.9% | 2.8%* | 0% | 1.3%§ | 5.7% | 1.8% | 0% | 2.4% |
Healthy weight (18.5 to < 25) | 38.5 | 43.8 | 17.7 | 40.1 | 25.9 | 46.4 | 12.3 | 31.2 | 22.6 | 24.0 | 22.9 | 22.4 |
Overweight, not obese (≥ 25 to < 30) | 28.8 | 24.6 | 25.3 | 29.0 | 22.5 | 25.0 | 30.9 | 24.9 | 13.5 | 23.6 | 26.1 | 19.4 |
Obese (≥ 30 to < 40) | 22.0 | 19.2 | 36.5 | 20.9 | 29.8 | 17.6 | 30.3 | 26.2 | 50.3 | 31.0 | 34.9 | 32.3 |
Severely obese (≥ 40) | 9.8 | 9.7 | 19.1 | 9.2 | 19.9 | 8.2 | 26.5 | 16.4 | 7.8 | 19.6 | 16.1 | 23.5 |
Vigorous leisure time activity: column %a | ||||||||||||
Unable to be active | 2.5% | 1.0%* | 7.9% | 2.1% | 6.3% | 0.2%* | 2.7% | 0.7% | 12.3% | 2.4% | 13.2% | 14.7% |
Inactive | 71.1 | 52.6 | 73.8 | 70.9 | 63.8 | 51.0 | 74.8 | 55.6 | 64.5 | 65.8 | 80.7 | 70.3 |
Some activity | 2.2 | 3.1 | 1.5 | 2.2 | 3.1 | 3.1 | 0 | 4.1 | 5.9 | 4.2 | 0 | 1.3 |
Regular activity | 23.4 | 42.2 | 16.4 | 23.9 | 26.1 | 44.6 | 21.7 | 38.7 | 17.3 | 26.7 | 6.1 | 13.2 |
Light or moderate leisure time activity: column %a | ||||||||||||
Unable to be active | 1.4% | 0.7%* | 6.3% | 1.1% | 4.2% | 0.1%* | 1.3% | 0.1% | 8.5% | 1.2% | 13.2% | 10.6% |
Inactive | 46.4 | 39.3 | 45.5 | 46.5 | 43.0 | 38.7 | 45.5 | 33.5 | 44.5 | 42.2 | 46.2 | 53.0 |
Some activity | 2.0 | 1.9 | 1.3 | 2.0 | 2.1 | 1.9 | 0.7 | 3.2 | 3.6 | 2.0 | 0 | 1.2 |
Regular activity | 49.0 | 56.4 | 46.6 | 49.2 | 49.0 | 57.4 | 51.6 | 61.1 | 43.4 | 52.8 | 40.5 | 34.0 |
p values for differences between paired columns
p ≤ 0.0001
p ≤ 0.001
p ≤ 0.01
p ≤ 0.05
CPD = chronic physical disability
Other and missing responses not shown
Among only women who are currently pregnant, women with CPD are significantly more likely to smoke cigarettes every day: 12.2% compared with 6.3% for pregnant women without CPD (Table 2, p ≤ 0.001). Among women who are all currently pregnant, only 17.7% of those with CPD have BMIs in the healthy range, compared with 40.1% of women without CPD (p ≤ 0.0001). No statistically significant differences were found relating to leisure time physical activity between pregnant women with and without CPD. Perhaps because of small numbers of cases, few significant differences occur within each of the three CPD severity levels by current pregnancy status.
Table 3 shows self-reports of the seven mental health problems for subgroups of women categorized by current pregnancy and CPD as in Table 2. Across all women regardless of CPD, those who are currently pregnant are less likely to report specific mental health problems, although certain differences are not statistically significant (Table 3). Among women who are all currently pregnant, those with CPD are significantly more likely to report any emotional problems, 66.6% compared with 29.7% among women without CPD (p ≤ 0.0001). Table 3 also shows the percent of women who report that mental health conditions contributed to their functional impairment, in addition to physical health problems: 6.8% of pregnant women with CPD compared with 12.8% of women who are not pregnant.
Table 3.
Characteristics | All women | Pregnant women only | Non-pregnant women only | Women with CPD by severity | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3–5 | ||||||||||
Pregnant | CPD | CPD | Pregnant | Pregnant | Pregnant | |||||||
Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | |
Sample size: total number | 1,685 | 45,944 | 128 | 1,557 | 5,915 | 40,029 | 62 | 2,022 | 34 | 1,677 | 32 | 2,216 |
% of total sample in yes/no columns | 3.5% | 96.5% | 7.6% | 92.4% | 12.9% | 87.1% | 2.6% | 97.4% | 1.8% | 98.2% | 1.5% | 98.5% |
Mental health problems (%) | ||||||||||||
“So sad that nothing could cheer you up”a | 10.5% | 12.2%§ | 28.1% | 9.2%* | 32.3% | 9.3%* | 17.9% | 20.0% | 27.2% | 30.4% | 47.0% | 46.0% |
“Nervous”a | 17.1 | 19.4§ | 35.7 | 15.7* | 39.8 | 16.4* | 25.5 | 33.0 | 41.3 | 37.5 | 48.6 | 48.3 |
“Restless or fidgety”a | 18.2 | 19.9 | 44.5 | 16.2* | 46.2 | 16.0* | 40.1 | 37.9 | 43.0 | 44.4 | 53.6 | 55.8 |
“Hopeless”a | 4.1 | 7.1* | 18.0 | 3.0* | 21.7 | 4.9* | 12.1 | 12.9 | 13.8 | 20.0 | 32.3 | 31.6 |
“That everything was an effort”a | 16.1 | 15.5 | 44.6 | 13.9* | 40.3 | 11.9* | 45.2 | 30.3 | 42.5 | 35.8 | 45.5 | 53.7 |
“Worthless”a | 2.9 | 5.5* | 12.6 | 2.2 | 19.1 | 3.6* | 8.1 | 11.3 | 13.0 | 18.2 | 20.1 | 27.6 |
These feelings “interfere[d]” with “life or activities” | 8.4 | 11.4§ | 32.2 | 6.6* | 34.1 | 8.1* | 21.6 | 23.6 | 35.0 | 29.5 | 48.6 | 48.1 |
Chronic mental health condition mentioned as contributing to functional limitationc | NA | NA | 6.3 | NA | 12.8 | NA | 2.4 | 5.6 | 3.6 | 10.9 | 15.6 | 21.4 |
Any emotional problema | 32.2 | 34.0 | 66.6 | 29.7* | 66.0 | 29.3* | 64.9 | 57.8 | 65.3 | 64.4 | 70.7 | 75.4 |
p values for differences between paired columns
p ≤ 0.0001
p ≤ 0.001
p ≤ 0.01
p ≤ 0.05
CPD = chronic physical disability NA = not applicable
during past 30 days, experienced this emotion “all,” “most,” or “some of the time”
interfered “a lot” or “some”
among women with mobility disability only, condition described as chronic reported as contributing to functional limitations
any of the 6 emotional problems listed above
Multivariable Regression Results
As described in the methods, we conducted three sets of multivariable logistic regressions to predict five outcomes representing health risks (overall fair or poor health, current smoking, obesity, vigorous leisure time activity, and any emotional problem) accounting for sociodemographic characteristics and CPD (Table 4), current pregnancy (Table 5), and CPD and current pregnancy (Table 6). In many instances, the sociodemographic variables have strong associations with the five outcomes. After accounting for sociodemographic factors, CPD is significantly associated with all five outcomes, especially reports of fair or poor health with an AOR (95% CI) = 8.4 (7.6, 9.2, Table 4). In contrast, after controlling for the sociodemographic variables, current pregnancy is significantly associated with lower current smoking and leisure time activity; it is also associated with higher BMI, although as noted earlier, because NHIS did not ask for pre-pregnancy weight, that association requires cautious interpretation (Table 5). The full models control for both CPD and current pregnancy, as well as sociodemographic characteristics (Table 6). In these models, CPD is significantly associated only with self-reported fair or poor health and emotional problems, with AOR respectively of 6.9 (3.5, 13.7) and 3.6 (2.2, 6.0). In contrast, pregnancy is significantly associated only with current smoking (AOR = 0.3 [0.2, 0.6]), obesity (AOR = 2.4 [1.5, 3.9]), and vigorous leisure time physical activity (AOR = 0.4 [0.2, 0.8]).
Table 4.
Health behavior or condition, adjusted odds ratio (95% confidence interval) | |||||
---|---|---|---|---|---|
Overall health fair or poor | Current smoker | Obese | Vigorous leisure time physical activity | Any mental health problem | |
Age category | |||||
18–24 (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
25–29 | 1.6 (1.3, 2.0) | 1.8 (1.6, 2.1) | 1.6 (1.5, 1.8) | 0.8 (0.7, 0.9) | 1.0 (0.9, 1.1) |
30–34 | 1.9 (1.5, 2.3) | 1.6 (1.4, 1.8) | 1.9 (1.8, 2.1) | 0.7 (0.7, 0.8) | 1.0 (0.9, 1.1) |
35–39 | 2.4 (1.9, 2.8) | 1.5 (1.3, 1.7) | 2.2 (2.0, 2.4) | 0.7 (0.6, 0.7) | 0.9 (0.8, 1.0) |
40–44 | 2.5 (2.1, 3.0) | 1.5 (1.3, 1.7) | 2.1 (1.9, 2.4) | 0.7 (0.6, 0.7) | 0.8 (0.7, 0.9) |
45–49 | 2.7 (2.2, 3.2) | 1.5 (1.4, 1.7) | 2.0 (1.8, 2.2) | 0.6 (0.6, 0.7) | 0.8 (0.7, 0.9) |
Race | |||||
White only (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Black only | 1.5 (1.3, 1.6) | 0.5 (0.5, 0.6) | 1.8 (1.7, 2.0) | 0.6 (0.6, 0.7) | 0.9 (0.9, 1.0) |
Asian only | 0.9 (0.7, 1.2) | 0.2 (0.2, 0.3) | 0.4 (0.3, 0.5) | 0.5 (0.5, 0.6) | 0.7 (0.7, 0.8) |
Other race + multiple | 1.2 (1.0, 1.5) | 1.0 (0.9, 1.2) | 1.3 (1.1, 1.5) | 1.0 (0.9, 1.2) | 1.2 (1.0, 1.5) |
Ethnicity | |||||
Hispanic | 1.1 (1.0, 1.2) | 0.2 (0.2, 0.2) | 1.2 (1.1, 1.3) | 0.7 (0.6, 0.7) | 0.7 (0.7, 0.8) |
Not Hispanic (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Education | |||||
Less than high school | 1.5 (1.3, 1.7) | 1.2 (1.1, 1.4) | 1.0 (0.9, 1.1) | 0.7 (0.6, 0.8) | 1.1 (1.0, 1.2) |
High school (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Some college, associate's degree | 0.8 (0.7, 0.9) | 0.6 (0.6, 0.7) | 0.9 (0.8, 1.0) | 1.8 (1.7, 1.9) | 1.0 (1.0, 1.1) |
College degree and higher education | 0.3 (0.3, 0.4) | 0.2 (0.2, 0.2) | 0.5 (0.5, 0.6) | 3.0 (2.8, 3.2) | 0.7 (0.7, 0.8) |
Household income | |||||
Below federal poverty level | 2.3 (2.1, 2.5) | 1.6 (1.4, 1.7) | 1.1 (1.0, 1.2) | 0.7 (0.7, 0.8) | 1.5 (1.4, 1.6) |
Above poverty level (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Chronic physical disability | |||||
No CPD (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
CPD | 8.4 (7.6, 9.2) | 1.8 (1.7, 2.0) | 2.3 (2.2, 2.5) | 0.6 (0.5, 0.6) | 4.3 (4.0, 4.6) |
Table 5.
Health behavior or condition, adjusted odds ratio (95% confidence interval) | |||||
---|---|---|---|---|---|
Overall health fair or poor | Current smoker | Obese | Vigorous leisure time physical activity | Any mental health problem | |
Age category | |||||
18–24 (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
25–29 | 1.8 (1.5, 2.2) | 1.9 (1.7, 2.2) | 1.7 (1.5, 1.8) | 0.8 (0.7, 0.9) | 1.1 (1.0, 1.2) |
30–34 | 2.3 (2.0, 2.8) | 1.7 (1.5, 1.9) | 2.0 (1.9, 2.2) | 0.7 (0.6, 0.8) | 1.1 (1.0, 1.2) |
35–39 | 3.3 (2.7, 3.9) | 1.6 (1.4, 1.8) | 2.4 (2.2, 2.7) | 0.6 (0.6, 0.7) | 1.0 (1.0, 1.1) |
40–44 | 3.9 (3.2, 4.6) | 1.6 (1.4, 1.8) | 2.5 (2.2, 2.7) | 0.6 (0.5, 0.7) | 1.0 (0.9, 1.1) |
45–49 | 4.8 (4.0, 5.7) | 1.7 (1.5, 1.9) | 2.4 (2.2, 2.6) | 0.5 (0.5, 0.6) | 1.1 (1.0, 1.2) |
Race | |||||
White only (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Black only | 1.3 (1.2, 1.5) | 0.5 (0.5, 0.6) | 1.8 (1.7, 1.9) | 0.6 (0.6, 0.7) | 0.9 (0.9, 1.0) |
Asian only | 0.6 (0.5, 0.8) | 0.2 (0.2, 0.3) | 0.4 (0.3, 0.4) | 0.6 (0.5, 0.6) | 0.7 (0.6, 0.8) |
Other race + multiple | 1.4 (1.1, 1.7) | 1.1 (0.9, 1.3) | 1.3 (1.1, 1.6) | 1.0 (0.8, 1.1) | 1.3 (1.1, 1.5) |
Ethnicity | |||||
Hispanic | 0.8 (0.7, 0.9) | 0.2 (0.2, 0.2) | 1.1 (1.0, 1.2) | 0.7 (0.6, 0.7) | 0.7 (0.6, 0.7) |
Not Hispanic (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Education | |||||
Less than high school | 1.6 (1.4, 1.8) | 1.3 (1.2, 1.4) | 1.0 (1.0, 1.1) | 0.7 (0.6, 0.8) | 1.1 (1.0, 1.2) |
High school (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Some college, associate's degree | 0.7 (0.7, 0.8) | 0.6 (0.6, 0.7) | 0.9 (0.8, 1.0) | 1.8 (1.7, 1.9) | 1.0 (0.9, 1.1) |
College degree and higher education | 0.3 (0.2, 0.3) | 0.2 (0.2, 0.2) | 0.5 (0.5, 0.5) | 3.2 (3.0, 3.4) | 0.6 (0.6, 0.7) |
Household income | |||||
Below federal poverty level | 2.8 (2.5, 3.1) | 1.7 (1.5, 1.8) | 1.2 (1.1, 1.3) | 0.7 (0.6, 0.8) | 1.6 (1.5, 1.8) |
Above poverty level (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Current pregnancy | |||||
Not pregnant (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Pregnant | 0.7 (0.6, 1.0) | 0.4 (0.3, 0.5) | 1.4 (1.2, 1.6) | 0.4 (0.3, 0.4) | 0.9 (0.8, 1.1) |
Table 6.
Health behavior or condition, adjusted odds ratio (95% confidence interval) | |||||
---|---|---|---|---|---|
Overall health fair or poor | Current smoker | Obese | Vigorous leisure time physical activity | Any mental health problem | |
Age category | |||||
18–24 (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
25–29 | 1.6 (1.4, 2.0) | 1.9 (1.7, 2.1) | 1.6 (1.5, 1.8) | 0.8 (0.8, 0.9) | 1.0 (0.9, 1.1) |
30–34 | 1.9 (1.5, 2.2) | 1.6 (1.4, 1.8) | 1.9 (1.8, 2.1) | 0.7 (0.7, 0.8) | 1.0 (0.9, 1.1) |
35–39 | 2.3 (1.9, 2.8) | 1.4 (1.3, 1.6) | 2.2 (2.0, 2.4) | 0.7 (0.6, 0.7) | 0.9 (0.8, 1.0) |
40–44 | 2.4 (2.0, 2.9) | 1.5 (1.3, 1.6) | 2.2 (2.0, 2.4) | 0.6 (0.6, 0.7) | 0.8 (0.7, 0.9) |
45–49 | 2.6 (2.2, 3.1) | 1.5 (1.3, 1.7) | 2.0 (1.8, 2.2) | 0.6 (0.5, 0.6) | 0.8 (0.7, 0.9) |
Race | |||||
White only (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Black only | 1.5 (1.3, 1.7) | 0.5 (0.5, 0.6) | 1.8 (1.7, 2.0) | 0.6 (0.6, 0.7) | 0.9 (0.9, 1.0) |
Asian only | 0.9 (0.7, 1.2) | 0.2 (0.2, 0.3) | 0.4 (0.3, 0.5) | 0.5 (0.5, 0.6) | 0.7 (0.7, 0.8) |
Other race + multiple | 1.2 (1.0, 1.5) | 1.0 (0.9, 1.2) | 1.3 (1.1, 1.5) | 1.0 (0.9, 1.2) | 1.2 (1.0, 1.5) |
Ethnicity | |||||
Hispanic | 1.1 (1.0, 1.2) | 0.2 (0.2, 0.2) | 1.2 (1.1, 1.3) | 0.7 (0.6, 0.7) | 0.7 (0.7, 0.8) |
Not Hispanic (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Education | |||||
Less than high school | 1.5 (1.3, 1.7) | 1.2 (1.1, 1.4) | 1.0 (0.9, 1.1) | 0.7 (0.6, 0.8) | 1.1 (1.0, 1.2) |
High school (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Some college, associate's degree | 0.8 (0.7, 0.9) | 0.6 (0.6, 0.7) | 0.9 (0.8, 1.0) | 1.8 (1.6, 1.9) | 1.0 (1.0, 1.1) |
College degree and higher education | 0.3 (0.3, 0.4) | 0.2 (0.2, 0.2) | 0.5 (0.5, 0.6) | 3.0 (2.8, 3.3) | 0.7 (0.7, 0.8) |
Household income | |||||
Below federal poverty level | 2.3 (2.1, 2.5) | 1.6 (1.4, 1.7) | 1.1 (1.0, 1.2) | 0.7 (0.7, 0.8) | 1.5 (1.4, 1.6) |
Above poverty level (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Current pregnancy | |||||
Not pregnant (reference) | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
Pregnant | 0.6 (0.4, 1.2) | 0.3 (0.2, 0.6) | 2.4 (1.5, 3.9) | 0.4 (0.2, 0.8) | 0.8 (0.5, 1.3) |
Chronic physical disability | |||||
No CPD (reference) | 1.0 | 1.0 | 1.0 | v | 1.0 |
CPD | 6.9 (3.5, 13.7) | 1.3 (0.7, 2.5) | 1.5 (0.9, 2.4) | 0.7 (0.3, 1.3) | 3.6 (2.2, 6.0) |
Discussion
Across women regardless of disability, women who are currently pregnant are much more likely to report better overall health than are nonpregnant women. Pregnant women are also much less likely to be current smokers than nonpregnant women. Perhaps not surprisingly, pregnant women are less likely than other women to engage in any leisure time physical activity. They are also less likely to have a healthy weight, although this finding requires cautious interpretation: NHIS records only a single weight per respondent and therefore does not separate pregnancy-related weight gains from pre-pregnancy weight when calculating BMIs.
Thus, on these various indicators of physical health risks – with the exception of attributes potentially confounded by the effects of pregnancy (weight and leisure time physical activity) – pregnant women appear to have better overall health than do non-pregnant women, even controlling for age and other sociodemographic characteristics. Nonetheless, even among this relatively “healthy” subgroup – women who are currently pregnant – those women who have CPD appear to have higher rates of health risk factors than women without CPD. This observation among currently pregnant women parallels findings across all women regardless of pregnancy: that women with CPD have more health risk factors and worse overall health than women without CPD.
Among women who are currently pregnant, women with CPD are much more likely than nondisabled women to be active smokers and much less likely to have healthy weights or pursue leisure time physical activities. Approximately 56% of currently pregnant women with CPD report being obese or severely obese, compared with only 30% of currently pregnant women without CPD. This comparison contrasts only pregnant women with other pregnant women, and it suggests that women with CPD are much more likely to have excess weight than women without CPD.
As noted above, interpreting these findings is hampered by limitations in our data source. Because NHIS does not collect information on pre-pregnancy weights, we cannot know if the BMI differences between pregnant women with and without CPD reflect higher pre-pregnancy BMIs, greater weight gain in pregnancy, or both. Moreover, because NHIS only asks whether women are “currently pregnant,” we have no data on trimester of pregnancy that could help distinguish among these possibilities (among women in the first trimester, high BMIs would be less appropriately attributed to weight gain, which manifests typically in later trimesters, and would more likely reflect pre-pregnancy BMI). However, because data among nonpregnant women with CPD indicate substantially higher BMIs than among women without CPD, we strongly suspect that pre-pregnancy weight contributes a large part to the BMI pattern we observed among currently pregnant women with CPD.
Since NHIS relies on self-reported information, one important question is whether there are any biases in weight reporting between women with and without CPD. It is possible that women with severe CPD who have trouble getting onto standard weight scales might under-report their weights. For example, without wheelchair accessible weight scales, persons who use wheelchairs because of disability acquired in adulthood often resort to estimating their weight, sometimes semi-joking, to be similar to that from before their disability's onset – and lower than their actual weights.(30, 31) Thus, we suspect any bias in reporting body weight would involve women with CPD giving weights lower than their actual weight. Therefore, this striking differential we observe in obesity rates between currently pregnant women with and without CPD is likely real, although the precise magnitude of the difference is unclear. Understanding the details of changes in BMI during pregnancy for all women, including women with CPD, represents an important opportunity for future research and NHIS surveys.
Among the attributes we examined overall mental health is the one area that did not differ significantly by current pregnancy status, although differences were observed for some individual mental health items. In bivariable analyses, women who are currently pregnant are generally much less likely to report mental health problems, although again only some of these differences are statistically significant. In the multivariable models involving all women and adjusting for various sociodemographic characteristics, however, current pregnancy was not significantly related to having any mental health problem. In spite of that observation, among only women who are currently pregnant, women with CPD report significantly higher rates of mental health problems. For instance, among pregnant women, the percentages of women with CPD reporting feeling “worthless” and “hopeless” are both 6 times the percentages reported by women without CPD; similarly the percentage reporting “feeling so sad that nothing could cheer [them] up” is 3.5 times higher and feeling that “everything was an effort” is 3.2 times as high for women with versus without CPD.
Thus, although women with CPD who are currently pregnant may have “healthier” attributes, in general, than nonpregnant women with CPD, women with CPD who are currently pregnant appear to have much higher health risks than currently pregnant women without CPD. To the extent that smoking,(8–13) obesity,(15–21) and mental health conditions (23, 24) affect pregnancy experiences and outcomes, currently pregnant women with CPD face higher likelihood of problems than women without CPD. These concerns underscore the need for clinicians caring for women with CPD before, during, and after pregnancy to anticipate and address these risks.
Intensive pre-conception care to directly address smoking, excess weight, nutrition, and emotional health may improve the chances of good pregnancy experiences and outcomes for all women, but given the prevalences described here, especially women with CPD. Addressing such common health risks as excess body weight, smoking, and lacking exercise might require different approaches for women with versus without CPD. Although some women with CPD are athletic and can perform strenuous physical exercise, many other women with CPD are not physically capable of this level of activity. Therefore, they are at risk of energy imbalance – consuming more calories than they can expend. This imbalance complicates efforts to control and reduce weight. During pregnancy, nutritional counseling to identify BMI-specific targets for weight gain, for example, may optimize outcomes for women with CPD. Smoking cessation interventions should be similar to those for nondisabled women. However, analyses from earlier versions of NHIS indicate that physicians are significantly less likely to ask women with major movement disabilities about their smoking histories than they are to ask nondisabled women.(7) NHIS data do not reveal reasons for this disparity, but it raises questions about how physicians might think about smoking cessation among patients with major CPD. Finally, our findings suggest that post-partum screening for depression may be especially important for women with CPD given the relatively high prevalence of self-reported mental health concerns.
In addition to the concerns noted above about the BMI data, this study has significant other limitations relating to the NHIS. With cross-sectional survey data, we can only explore statistical associations; we cannot make causal inferences. Notably, NHIS contains no information about either maternal or neonatal pregnancy outcomes. The quality of the pregnancy indicator, functional difficulties (source of CPD information), and risk factor information is unknown. Although NHIS instructions indicated that women should not report functional impairments related to pregnancy, some did. Studies suggest that women may not accurately report smoking during pregnancy,(32, 33) although there is no reason to expect nonresponse bias to related to CPD. Respondents may either over- or underreport mental health concerns for diverse reasons, some of which might relate to perceptions of societal attitudes toward disability. Finally, although we used multiple years of data, the numbers of women with CPD, especially those who report pregnancy, are relatively small. These small numbers prevent more in-depth analyses.
In conclusion, women with CPD who are currently pregnant have higher rates of tobacco use, obesity, and mental health problems – and worse overall health – than do currently pregnant women without CPD. These factors could contribute to worse birth outcomes and maternal pregnancy experiences for women with CPD. Clinicians caring for women with CPD who want to become pregnant should address these risk factors in counseling women to optimize their overall health before pregnancy. Addressing these risk factors during and immediately after pregnancy is also important, in order to offer women with disabilities the best opportunity to have both healthy babies and good maternal health outcomes.
Acknowledgments
FUNDING: Eunice Kennedy Shriver National Institute for Child Health and Human Development, Grant No. 5R21HD068756-02
Footnotes
AUTHOR CONFLICTS OF INTEREST: None
References
- 1.Altman B, Bernstein A. Disability and Health in the United States, 2001–2005. National Center for Health Statistics; Hyattsville, MD: 2008. [Google Scholar]
- 2.Chevarley FM, Thierry JM, Gill CJ, Ryerson AB, Nosek MA. Health, preventive health care, and health care access among women with disabilities in the 1994–1995 National Health interview survey, supplement on disability. Womens Health Issues. 2006 Nov-Dec;16(6):297–312. doi: 10.1016/j.whi.2006.10.002. [DOI] [PubMed] [Google Scholar]
- 3.Robinson-Whelen S, Taylor HB, Hughes RB, Nosek MA. Depressive symptoms in women with physical disabilities: Identifying correlates to inform practice. Arch Phys Med Rehabil. 2013 Dec;94(12):2410–6. doi: 10.1016/j.apmr.2013.07.013. [DOI] [PubMed] [Google Scholar]
- 4.Hughes RB, Taylor HB, Robinson-Whelen S, Nosek MA. Stress and women with physical disabilities: Identifying correlates. Womens Health Issues. 2005 Jan-Feb;15(1):14–20. doi: 10.1016/j.whi.2004.09.001. [DOI] [PubMed] [Google Scholar]
- 5.Hughes RB, Robinson-Whelen S, Taylor HB, Petersen NJ, Nosek MA. Characteristics of depressed and nondepressed women with physical disabilities. Arch Phys Med Rehabil. 2005 Mar;86(3):473–9. doi: 10.1016/j.apmr.2004.06.068. [DOI] [PubMed] [Google Scholar]
- 6.Wisdom JP, McGee MG, Horner-Johnson W, Michael YL, Adams E, Berlin M. Health disparities between women with and without disabilities: A review of the research. Soc Work Public Health. 2010 May;25(3):368–86. doi: 10.1080/19371910903240969. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Iezzoni LI, McCarthy EP, Davis RB, Harris-David L, O'Day B. Use of screening and preventive services among women with disabilities. Am J Med Qual. 2001 Jul-Aug;16(4):135–44. doi: 10.1177/106286060101600405. [DOI] [PubMed] [Google Scholar]
- 8.Tong VT, Jones JR, Dietz PM, D'Angelo D, Bombard JM. Centers for Disease Control and Prevention (CDC). Trends in smoking before, during, and after pregnancy - pregnancy risk assessment monitoring system (PRAMS), United States, 31 sites, 2000–2005. MMWR Surveill Summ. 2009 May 29;58(4):1–29. [PubMed] [Google Scholar]
- 9.Tong VT, Dietz PM, Morrow B, D'Angelo DV, Farr SL, Rockhill KM, England LJ. Centers for Disease Control and Prevention (CDC). Trends in smoking before, during, and after pregnancy--pregnancy risk assessment monitoring system, united states, 40 sites, 2000–2010. MMWR Surveill Summ. 2013 Nov 8;62(6):1–19. [PubMed] [Google Scholar]
- 10.Dietz PM, England LJ, Shapiro-Mendoza CK, Tong VT, Farr SL, Callaghan WM. Infant morbidity and mortality attributable to prenatal smoking in the U.S. Am J Prev Med. 2010 Jul;39(1):45–52. doi: 10.1016/j.amepre.2010.03.009. [DOI] [PubMed] [Google Scholar]
- 11.Adams EK, Melvin CL, Raskind-Hood C, Joski PJ, Galactionova E. Infant delivery costs related to maternal smoking: An update. Nicotine Tob Res. 2011 Aug;13(8):627–37. doi: 10.1093/ntr/ntr042. [DOI] [PubMed] [Google Scholar]
- 12.Kim SY, England LJ, Kendrick JS, Dietz PM, Callaghan WM. The contribution of clinic-based interventions to reduce prenatal smoking prevalence among US women. Am J Public Health. 2009 May;99(5):893–8. doi: 10.2105/AJPH.2008.144485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Lumley J, Chamberlain C, Dowswell T, Oliver S, Oakley L, Watson L. Interventions for promoting smoking cessation during pregnancy. Cochrane Database Syst Rev. 2009 Jul;8(3):CD001055. doi: 10.1002/14651858.CD001055.pub3. doi(3):CD001055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Mitra M, Lu E, Diop H. Smoking among pregnant women with disabilities. Womens Health Issues. 2012 Mar;22(2):e233–9. doi: 10.1016/j.whi.2011.11.003. [DOI] [PubMed] [Google Scholar]
- 15.Nohr EA, Villamor E, Vaeth M, Olsen J, Cnattingius S. Mortality in infants of obese mothers: Is risk modified by mode of delivery? Acta Obstet Gynecol Scand. 2012 Mar;91(3):363–71. doi: 10.1111/j.1600-0412.2011.01331.x. [DOI] [PubMed] [Google Scholar]
- 16.Cnattingius S, Villamor E, Johansson S, Edstedt Bonamy AK, Persson M, Wikstrom AK, Granath F. Maternal obesity and risk of preterm delivery. JAMA. 2013 Jun 12;309(22):2362–70. doi: 10.1001/jama.2013.6295. [DOI] [PubMed] [Google Scholar]
- 17.Ehrenberg HM, Mercer BM, Catalano PM. The influence of obesity and diabetes on the prevalence of macrosomia. Am J Obstet Gynecol. 2004 Sep;191(3):964–8. doi: 10.1016/j.ajog.2004.05.052. [DOI] [PubMed] [Google Scholar]
- 18.Kristensen J, Vestergaard M, Wisborg K, Kesmodel U, Secher NJ. Pre-pregnancy weight and the risk of stillbirth and neonatal death. BJOG. 2005 Apr;112(4):403–8. doi: 10.1111/j.1471-0528.2005.00437.x. [DOI] [PubMed] [Google Scholar]
- 19.Joy S, Istwan N, Rhea D, Desch C, Stanziano G. The impact of maternal obesity on the incidence of adverse pregnancy outcomes in high-risk term pregnancies. Am J Perinatol. 2009 May;26(5):345–9. doi: 10.1055/s-0028-1110084. [DOI] [PubMed] [Google Scholar]
- 20.Magann EF, Doherty DA, Sandlin AT, Chauhan SP, Morrison JC. The effects of an increasing gradient of maternal obesity on pregnancy outcomes. Aust N Z J Obstet Gynaecol. 2013 Feb 25; doi: 10.1111/ajo.12047. [DOI] [PubMed] [Google Scholar]
- 21.Minsart AF, Buekens P, De Spiegelaere M, Englert Y. Neonatal outcomes in obese mothers: A population-based analysis. BMC Pregnancy Childbirth. 2013 Feb 11;13:36. doi: 10.1186/1471-2393-13-36. 2393-13-36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Committee on Obstetric Practice Committee opinion no. 549. obesity in pregnancy. Obstet Gynecol. 2013;121:213–7. doi: 10.1097/01.aog.0000425667.10377.60. [DOI] [PubMed] [Google Scholar]
- 23.Gaillard A, Le Strat Y, Mandelbrot L, Keita H, Dubertret C. Predictors of postpartum depression: Prospective study of 264 women followed during pregnancy and postpartum. Psychiatry Res. 2014;215(2):341–6. doi: 10.1016/j.psychres.2013.10.003. [DOI] [PubMed] [Google Scholar]
- 24.Milgrom J, Gemmill AW, Bilszta JL, Hayes B, Barnett B, Brooks J, Ericksen J, Ellwood D, Buist A. Antenatal risk factors for postnatal depression: A large prospective study. J Affect Disord. 2008 May;108(1–2):147–57. doi: 10.1016/j.jad.2007.10.014. [DOI] [PubMed] [Google Scholar]
- 25.Institute of Medicine, Committee on Disability in America Board on Health Sciences Policy . In: The Future of Disability in America. Field MJ, Jette AM, editors. The National Academies Press; Washington, D.C.: 2007. [PubMed] [Google Scholar]
- 26.Iezzoni LI, Yu J, Wint AJ, Smeltzer SC, Ecker JL. Prevalence of current pregnancy among U.S. women with and without chronic physical disabilities. Med Care. 2013 Jun;51(6):555–62. doi: 10.1097/MLR.0b013e318290218d. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Iezzoni LI, Yu J, Wint AJ, Smeltzer SC, Ecker JL. Conditions causing disability and current pregnancy among US women with chronic physical disabilities. Med Care. 2014 Jan;52(1):20–5. doi: 10.1097/MLR.0000000000000015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Iezzoni LI, Yu J, Wint AJ, Smeltzer SC, Ecker JL. General health, health conditions, and current pregnancy among U.S. women with and without chronic physical disabilities. Disabil Health J. 2014;7(2):181–8. doi: 10.1016/j.dhjo.2013.12.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Division of Health Interview Statistics, National Center for Health Statistics. 2008 National Health Interview Survey (NHIS) NHIS Survey Description. Centers for Disease Control and Preventions, U.S. Department of Health and Human Services; Hyattsville, MD: Jun, 2009. Public Use Data Release. [Google Scholar]
- 30.Iezzoni LI, O'Day BL. More Than Ramps. A Guide to Improving Health Care Quality and Access for People with Disabilities. Oxford University Press; New York: 2006. [Google Scholar]
- 31.Iezzoni LI, Kilbridge K, Park ER. Physical access barriers to care for diagnosis and treatment of breast cancer among women with mobility impairments. Oncology Nursing Forum. 2010;37(6):711–7. doi: 10.1188/10.ONF.711-717. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Dietz PM, Homa D, England LJ, Burley K, Tong VT, Dube SR, Bernert JT. Estimates of nondisclosure of cigarette smoking among pregnant and nonpregnant women of reproductive age in the united states. Am J Epidemiol. 2011 Feb 1;173(3):355–9. doi: 10.1093/aje/kwq381. [DOI] [PubMed] [Google Scholar]
- 33.Tong VT, Dietz PM, Farr SL, D'Angelo DV, England LJ. Estimates of smoking before and during pregnancy, and smoking cessation during pregnancy: Comparing two population-based data sources. Public Health Rep. 2013 May-Jun;128(3):179–88. doi: 10.1177/003335491312800308. [DOI] [PMC free article] [PubMed] [Google Scholar]