Maternal and Child Health Journal

, Volume 16, Issue 1, pp 60–71

Chronic Diseases and Related Risk Factors among Low-Income Mothers

Authors

    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Patricia M. Dietz
    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Christine Galavotti
    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Lucinda J. England
    • Maternal and Infant Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Van T. Tong
    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Donald K. Hayes
    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
  • Brian Morrow
    • Applied Sciences Branch, Division of Reproductive HealthNational Center for Chronic Disease & Health Promotion, Centers for Disease Control & Prevention
Article

DOI: 10.1007/s10995-010-0717-1

Cite this article as:
Bombard, J.M., Dietz, P.M., Galavotti, C. et al. Matern Child Health J (2012) 16: 60. doi:10.1007/s10995-010-0717-1

Abstract

The aim is to describe the burden of chronic disease and related risk factors among low-income women of reproductive age. We analyzed population-based data from the 2005–2006 Pregnancy Risk Assessment Monitoring System (PRAMS) for 14,990 women with a live birth in 7 states. We examined the prevalence of selected chronic diseases and related risk factors (preexisting diabetes, gestational diabetes, chronic hypertension, pregnancy-induced hypertension, obesity, smoking or binge drinking prior to pregnancy, smoking or excessive weight gain during pregnancy, and postpartum depressive symptoms) by Federal Poverty Level (FPL) (≤100% FPL; 101–250% FPL; >250% FPL). Approximately one-third of women were low-income (≤100% FPL), one-third were near-low-income (101–250% FPL), and one-third were higher-income (>250% FPL). Compared to higher-income women, low-income women were significantly more likely to smoke before or during pregnancy (34.2% vs. 14.4%, and 24.8% vs. 5.4%, respectively), be obese (22.2% vs. 16.0%), experience postpartum depressive symptoms (23.3% vs. 7.9%), have 3 or more chronic diseases and/or related risk factors (28.1% vs. 14.4%) and be uninsured before pregnancy (48.9% vs. 4.8%). Low-income women of reproductive age experienced a higher prevalence of selected chronic diseases and related risk factors. Enhancing services for these women in publicly-funded family planning clinics may help reduce disparities in pregnancy and long-term health outcomes in the poor.

Keywords

PregnancyChronic diseasesPrevalencePoverty

Introduction

The top three leading causes of death among women in the United States—heart disease, cancer, and stroke [1] —are chronic diseases. Many chronic diseases can be prevented by modifying lifestyle risk factors such as physical inactivity, tobacco use, and unhealthy eating. Providing effective interventions early to women at risk can reduce subsequent mortality and morbidity, and has the added benefit of reducing maternal and fetal complications during pregnancy.

Early identification and treatment for women of reproductive age with or at risk for chronic diseases can be challenging for at least two reasons. First, these women generally feel well and are less likely to seek general medical care or preventive health services [2]. Second, many young women lack health insurance. In 2006, almost 18% of women aged 19–23 years were uninsured [3]. However, young women are likely to seek reproductive health services, and in fact, this is one of their primary reasons for seeking care [4, 5]. Because so many young women are uninsured and underinsured, publicly-funded reproductive health care providers, such as Title X-funded family planning clinics, could play a key role in screening, referring, and/or treating high-risk young women.

It is well-established that low-income individuals have a higher prevalence of many chronic diseases and related risk factors than higher-income individuals [6]. Little is known, however, about the prevalence of these conditions in low-income women of reproductive age. In the present study, we used population-based data of women who had recently delivered a live birth to estimate the burden of selected chronic diseases and related risk factors among women of reproductive age, according to different income levels. This information can be used to assess the potential benefits of expanding upon existing reproductive health services to include screening, treatment, and referral for various chronic diseases and related risk factors.

Methods

Data Source and Study Population

We analyzed data from the Pregnancy Risk Assessment Monitoring System (PRAMS) [7], an ongoing state-and population-based surveillance project of the Centers for Disease Control and Prevention (CDC) and state health departments. PRAMS collects information on maternal experiences and behaviors before, during, and after pregnancy.

States implementing PRAMS use a standardized, mixed-method data collection approach. Each month, a stratified systematic sample of 100–300 women who recently delivered a live-born infant is selected from the state’s birth certificate records. Women are mailed a questionnaire, 3–6 months after delivery. If the mother does not respond, a second and, in many states, a third questionnaire is mailed to her. If there is no response to the questionnaires, attempts are made to conduct a telephone interview. Each mother’s questionnaire is linked to her child’s birth certificate and data are weighted to adjust for sampling design, noncoverage, and nonresponse. We analyzed 2005–2006 PRAMS survey data and linked birth certificate data for states which (1) achieved a 70% response rate and (2) implemented the 2003 revised birth certificate: Florida, Nebraska, New York (excluding New York City), Ohio, South Carolina, Washington, and Vermont. Response rates ranged from 70.1 to 83.1%.

Definitions of Variables

This study was limited to chronic diseases and related risk factors as reported on the PRAMS questionnaire or linked birth certificate. The PRAMS questionnaire included questions addressing preexisting diabetes, smoking before and during pregnancy, binge drinking before pregnancy, prepregnancy body mass index (BMI), and postpartum depressive symptoms. The birth certificate included information on preexisting diabetes, GDM1 (diabetes first diagnosed during pregnancy), chronic hypertension, PIH1 (hypertension first diagnosed during pregnancy), smoking before or during pregnancy, and weight gain during pregnancy. Birth certificate data on diabetes and hypertension were not available for New York.

Both the PRAMS survey and the birth certificate were ascertained for preexisting diabetes and smoking status before and during pregnancy. Women who reported smoking cigarettes during the 3 months prior to pregnancy on either data source were classified as having smoked before pregnancy. Women who reported smoking during the last 3 months of pregnancy on PRAMS or smoking during any trimester on the birth certificate were classified as having smoked during pregnancy. Women who reported that they did not consume alcohol during the past 2 years were classified as non-drinkers; women who reported drinking during the past 2 years but not drinking 5 or more drinks at one or more sittings prior to pregnancy were classified as drinkers, non-binge; and women who reported drinking during the past 2 years and drinking 5 or more drinks at one sitting at least once during the 3 months before pregnancy were classified as binge-drinkers.

Prepregnancy body mass index (BMI) was calculated from self-reported height and prepregnancy weight. BMI categories were classified according to the National Heart Lung and Blood Institute (NHLBI): underweight (<18.5 kg/m2); normal (18.5–24.9 kg/m2); overweight (25.0–29.9 kg/m2); and obese (≥30.0 kg/m2). [8] Women’s total weight gain during pregnancy was calculated from information on prepregnancy weight and delivery weight on the birth certificate. Using the 2009 Institute of Medicine (IOM) weight-gain recommendations, we created a weekly weight-gain algorithm according to the gestational age at delivery and classified women as having weight gain below, within, or above the IOM recommendation according to their corresponding prepregnancy BMIs (see Appendix) [9]. Women who indicated they always or often felt down, depressed, or hopeless or that they had little interest in activities since their new baby was born were classified as having postpartum depressive symptoms. Data on postpartum depressive symptoms were not available for Florida. Finally, we calculated the total number of chronic diseases and related risk factors for states with complete data. Total household income (before taxes) prior to delivery was self-reported as a categorical response on the PRAMS questionnaire. We converted income levels into a percentage of the federal poverty level (FPL) using published charts of the federal poverty cut-off’s by family size; 2004 U.S. Department of Health and Human Services Poverty Guidelines for PRAMS 2005 births and 2005 poverty guidelines for PRAMS 2006 births (http://aspe.hhs.gov/POVERTY/figures-fed-reg.shtml).

Since PRAMS income level responses were categorical, a midpoint was selected for each category. To adjust for family size, midpoint income was then divided by the total number of persons living in the household. We created the following three FPL categories: low-income (≤100% FPL), near-low-income (101–250% FPL), and higher-income (>250% FPL) based on Title X payment fees [10].

Maternal age, education, marital status, and race/ethnicity were obtained from the birth certificate. Race/ethnicity data were not available for Vermont. Prepregnancy insurance status and pregnancy intention status were obtained from the PRAMS survey. Women who reported that they wanted to be pregnant (either sooner or during time of conception) were classified as having an intended pregnancy and women who did not want to be pregnant or be pregnant at a later time were classified as having an unintended pregnancy. Initiation of prenatal care by trimester was first obtained from the PRAMS survey and, if missing, from the birth certificate.

Statistical Analysis

Analyses were conducted in SUDAAN Version 10, and the standard errors adjusted for the complex sampling survey design of PRAMS. All data were weighted to represent live births delivered in each respective state. First, we used chi-square tests to assess differences between women excluded due to missing information on FPL and women who were included, comparing demographics, other background characteristics, and chronic diseases and related risk factors. Statistical significance was set at P < .05. Second, we calculated the prevalence and 95% confidence intervals (CIs) of the same factors by FPL categories. Prevalence estimates for which the 95% CI did not overlap between FPL categories were considered statistically different from one another. We conducted a sensitivity analysis to assess the effect of missing income level data on the estimated prevalence of chronic disease and related risk factors. In the analysis, prevalence estimates of chronic disease and related risk factors were calculated with the assumption that women missing income were low-income. We made this assumption because women with missing income were similar to those who reported low income with respect to demographic and background characteristics. The results of this analysis were compared with the analysis that excluded women with missing income. Finally, to determine if FPL was significantly associated with individual chronic diseases and related risk factors, we conducted multivariate analyses and adjusted for age, race/ethnicity, and education. Odds ratios and corresponding 95% CI’s were calculated. The PRAMS protocol was reviewed and approved by an Institutional Review Board at CDC and each participating state.

Results

Of the 16,437 women eligible for the study, 14,990 were included in the analysis, and 1,447 (8%) were excluded due to missing information on income. Compared with women included in the analysis, excluded women were significantly younger and less educated; were more likely to be unmarried, black non-Hispanic, Hispanic, or Asian/Pacific Islander; uninsured; to have had an unintended pregnancy; and to have initiated prenatal care later. They were also less likely to have smoked before pregnancy, been a binge drinker, have been obese before pregnancy, or to have had GDM than women included in the study (Table 1).
Table 1

Prevalence of demographic, other background characteristics, chronic disease risk factors and conditions of women among respondents excluded or included in analysis and who delivered a live birth in 7 states, PRAMS 2005–2006

 

Missing income information (excluded from analysis) (n = 1,447)

Complete income information (included in analysis) (n = 14,990)

 

%

%

P valuea

Totalb

8.0

92.0

 

Age (yrs)

 <20

24.8

8.9

.0000

 20–24

30.6

23.7

 

 25–34

32.3

51.5

 

 ≥35

12.3

15.9

 

Education (yrs)

 <12

45.2

16.5

.0000

 12

29.8

26.4

 

 >12

24.9

57.1

 

Marital status

 Not married

57.2

35.4

.0000

 Married

42.8

64.6

 

Race/ethnicityc

 White, non-Hispanic

40.0

64.7

.0000

 Black, non-Hispanic

20.9

13.5

 

 Hispanic

33.0

15.6

 

 Indian

0.5

0.6

 

 Asian/Pacific Islander

4.4

3.4

 

 Other

1.2

2.2

 

Prepregnancy insurance status

 Insured

57.1

73.3

.0000

 Uninsured

42.9

26.7

 

Pregnancy intention

 Intended

52.7

58.9

.0094

 Unintended

47.3

41.1

 

Initiation of prenatal care

 1st trimester

75.0

88.8

.0000

 2nd trimester

21.5

9.7

 

 3rd trimester or none

3.5

1.5

 

Prepregnancy

Preexisting diabetesc

 Yes

3.6

2.2

.1162

Chronic hypertensionc

 Yes

1.1

1.2

.7764

Smoking 3 months before pregnancy

 Yes

18.9

24.2

.0058

Binge drinking 3 months before pregnancyd

 Binge drinker

8.2

18.5

.0000

 Non binge drinkers

30.5

47.6

 

 Non drinkers

61.3

33.9

 

Body mass index (BMI)

 Underweight (<18.5 kg/m2)

6.7

4.6

.0081

 Normal (18.5–24.9 kg/m2)

56.9

52.2

 

 Overweight (25.0–29.9 kg/m2)

21.9

23.2

 

 Obese (≥30.0 kg/m2)

14.5

20.0

 

During pregnancy

Gestational diabetesc

 Yes

1.2

4.2

.0000

Pregnancy induced hypertension d

 Yes

4.1

4.7

.5588

Smoking at any time during pregnancy

 Yes

13.6

14.9

.4242

Weight gaine

 Below IOM recommendation

18.9

17.3

.5288

 Within IOM recommendation

32.8

31.1

 

 Above IOM recommendation

48.4

51.5

 

Postpartum Conditions

Depressive symptomsc

 Always/often

19.0

14.8

.0637

 Sometimes/rarely or never

81.0

85.2

 

Total number of chronic diseases and risk factors

0

20.4

17.3

.6581

1

29.8

34.9

 

2

26.8

26.5

 

3+

23.0

21.3

 

Data are weighted to represent all live births for 7 states (Florida, Nebraska, New York, Ohio, South Carolina, Washington, Vermont)

aChi-square significance test

bRow percents presented for total only

cRace/ethnicity data not available from Vermont; preexisting diabetes, gestational diabetes, chronic hypertension, and pregnancy induced hypertension data not available from New York, and postpartum depressive symptoms data not available from Florida

dBinge drinkers included women who indicated drinking 5 or more drinks in 1 sitting prior to pregnancy, non binge drinkers indicated drinking during the last 2 years and either did not binge drink or drink at all prior to pregnancy

eBased on the 2009 Institute of Medicine (IOM) recommendations for women’s weight gain for a singleton, term pregnancy

The Prevalence of Demographic and Other Background Characteristics

Overall, 34.5% of women were low-income, 28.8% were near-low-income, and 36.7% were higher-income (Table 2). Compared with higher-income women, low-income women were significantly younger and less educated; were more likely to be unmarried, black non-Hispanic, Hispanic, or Indian; and were more likely to have been uninsured prior to pregnancy; to have had an unintended pregnancy; and to have initiated prenatal care later or not at all (Table 2).
Table 2

Prevalence of demographic and other background characteristics of women who delivered a live birth in 7 states by Federal Poverty Level (FPL), PRAMS 2005–2006

 

Low-income (0–100% FPL) (n = 5,621)

Near-low-income (101–250% FPL) (n = 4,340)

Higher-income (>250% FPL) (n = 5,029)

%

95% CI

%

95% CI

%

95% CI

Totala

34.5

33.3–35.8

28.8

27.6–30.0

36.7

35.4–37.9

Age (years)

 <20**

18.5*

16.9–20.2

7.1

6.0–8.4

1.1

0.8–1.7

 20–24**

37.9*

35.8–40.1

27.6

25.4–29.9

7.3

6.2–8.6

 25–34**

35.1*

33.0–37.3

51.7

49.2–54.2

66.8

64.8–68.9

 ≥35**

8.4*

7.2–9.8

13.6

12.0–15.3

24.7

22.9–26.6

Education (years)

 <12**

36.8*

34.7–39.0

11.9

10.3–13.8

1.2

0.8–1.8

 12

37.2*

35.1–39.4

32.8

30.4–35.2

11.1

9.8–12.7

 >12**

26.0*

24.1–28.0

55.3

52.8–57.8

87.7

86.1–89.1

Marital status

 Not married**

66.9*

64.8–69.0

34.2

31.9–36.6

6.8

5.8–8.0

 Married**

33.1*

31.0–35.2

65.8

63.4–68.1

93.2

92.0–94.2

Race/ethnicityb

 White, non-Hispanic**

44.4*

42.2–46.5

66.7

64.5–68.9

82.4

80.8–84.0

 Black, non-Hispanic**

23.0*

21.4–24.6

13.6

12.2–15.1

4.4

3.7–5.3

 Hispanic**

26.5*

24.6–28.5

14.0

12.3–15.9

6.6

5.4–7.9

 Indian

1.0*

0.8–1.2

0.6

0.4–0.8

0.2

0.1–0.4

 Asian/Pacific Islander

2.4*

1.8–3.1

3.0

2.3–3.9

4.7

4.0–5.5

Other

2.8

2.2–3.6

2.1

1.6–2.9

1.7

1.3–2.3

Prepregnancy insurance status

 Insured**

51.1*

48.9–53.4

72.1

69.8–74.3

95.2

94.1–96.1

 Uninsured**

48.9*

46.6–51.1

27.9

25.7–30.2

4.8

3.9–5.9

Pregnancy intention

 Intended**

41.1*

38.9–43.3

55.0

52.5–57.5

78.8

76.9–80.6

 Unintended**

58.9*

56.7–61.1

45.0

42.5–47.5

21.2

19.4–23.1

Initiation of prenatal care

 1st trimester**

78.8*

76.9–80.6

89.1

87.4–90.6

97.9

97.2–98.4

 2nd trimester**

18.3*

16.6–20.2

9.4

8.1–11.0

1.9

1.4–2.5

 3rd trimester or none

2.8*

2.2–3.6

1.4

0.9–2.2

0.3

0.1–0.5

Data are weighted to represent all live births in 7 states (Florida, Nebraska, New York, Ohio, South Carolina, Washington, Vermont)

* Significant differences observed, 95% confidence intervals do not overlap for low-income versus higher-income women

** Significant differences observed, 95% confidence intervals do not overlap between all 3 income groups

aRow percents presented for total only

bRace/ethnicity data not available from Vermont

The Prevalence of Chronic Diseases and Related Risk Factors

Compared with higher-income women, low-income women were more likely to have smoked before (34.2% vs. 14.4%) and during pregnancy (24.8% vs. 5.4%); have been obese before pregnancy (22.2% vs. 16.0%); and to experience postpartum depressive symptoms (23.3% vs. 7.9%); and have 3 or more chronic diseases and/or related risk factors (28.1% vs. 14.4%). Low-income and higher-income women had similar prevalences of chronic hypertension and pregnancy-induced hypertension, GDM, and excessive weight gain during pregnancy (Table 3). Compared with low-income women, near-low-income women had a lower prevalence of smoking before or during pregnancy and of postpartum depressive symptoms, but a higher prevalence compared with higher-income women (Table 3). Near-low-income women were more similar to low-income women with respect to the average number of chronic diseases and/or related risk factors (Fig. 1).
Table 3

Prevalence of chronic disease risk factors and conditions of women who delivered a live birth in 7 states by Federal Poverty Level (FPL), PRAMS 2005–2006

 

Low-income (0–100% FPL) (n = 5,621)

Near-low-income (101–250% FPL) (n = 4,340)

Higher-income (>250% FPL) (n = 5,029)

%

95% CI

%

95% CI

%

95% CI

Totala

34.5

33.3–35.8

28.8

27.6–30.0

36.7

35.4–37.9

Prepregnancy

Preexisting diabetesb

 Yes

2.9

2.2–3.9

2.2

1.5–3.1

1.5

1.0–2.2

Chronic hypertensionb

 Yes

0.8

0.5–1.1

2.1

1.4–3.0

0.9

0.6–1.4

Smoking 3 months before pregnancy

 Yes**

34.2*

32.1–36.4

24.9

22.7–27.1

14.4

12.9–16.0

Binge drinking 3 months before pregnancyc

 Binge drinker

16.5

14.9–18.3

18.8

16.9–20.8

20.0

18.3–21.8

 Non binge drinkers**

33.5*

31.4–35.7

46.2

43.7–48.7

61.9

59.8–64.0

 Non drinkers**

49.9*

47.7–52.2

35.0

32.7–37.5

18.1

16.5–19.8

Body Mass Index (BMI)

 Underweight (<18.5 kg/m2)

6.5*

5.4–7.9

4.7

3.6–5.9

2.9

2.3–3.7

 Normal (18.5–24.9 kg/m2)

47.2*

44.8–49.5

48.8

46.2–51.3

59.3

57.1–61.4

 Overweight (25.0–29.9 kg/m2)

24.1

22.2–26.2

23.9

21.8–26.1

21.8

20.0–23.7

 Obese (≥30.0 kg/m2)

22.2*

20.3–24.1

22.7

20.7–24.9

16.0

14.5–17.7

During pregnancy

Gestational diabetesb

 Yes

3.3

2.6–4.2

5.3

4.2–6.7

4.2

3.3–5.3

Pregnancy induced hypertensionb

 Yes

5.0

4.0–6.2

4.7

3.8–5.9

4.3

3.3–5.4

Smoking at any time during pregnancy

 Yes**

24.8*

22.9–26.8

15.0

13.3–16.9

5.4

4.5–6.5

Weight gaind

 Below IOM recommendation

18.6*

16.8–20.6

19.7

17.6–21.9

14.5

13.0–16.2

 Within IOM recommendation

29.7

27.4–32.1

31.3

28.8–33.9

32.2

30.0–34.4

 Above IOM recommendation

51.7

49.1–54.3

49.1

46.4–51.8

53.3

51.0–55.6

Postpartum Conditions

Depressive symptomsb

 Always/often**

23.3*

21.3–25.5

13.9

12.1–15.9

7.9

6.8–9.2

 Sometimes/rarely or never**

76.7*

74.5–78.7

86.1

84.1–87.9

92.1

90.8–93.2

Total number of chronic diseases and risk factors

0

13.3*

11.2–15.8

15.7

13.3–18.5

21.8

19.4–24.4

1

28.9*

25.8–32.1

34.2

30.8–37.7

40.5

37.5–43.6

2

29.7*

26.5–33.0

27.3

24.2–30.7

23.2

20.8–25.9

3+

28.1*

25.1–31.4

22.8

19.8–26.1

14.4

12.3–16.8

Data are weighted to represent all live births in 7 states (Florida, Nebraska, New York, Ohio, South Carolina, Washington, Vermont)

* Significant differences observed, 95% confidence intervals do not overlap for low-income vs. higher-income women

** Significant differences observed, 95% confidence intervals do not overlap between all 3 income groups

aRow percents presented for total only

bPreexisting diabetes, gestational diabetes, chronic hypertension, and pregnancy induced hypertension data not available from New York, and postpartum depressive symptoms data not available from Florida

cBinge drinkers included women who indicated drinking 5 or more drinks in 1 sitting prior to pregnancy, non binge drinkers indicated drinking during the last 2 years and either did not binge drink or drink at all prior to pregnancy

dBased on the 2009 Institute of Medicine (IOM) recommendations for women’s weight gain for a singleton, term pregnancy

https://static-content.springer.com/image/art%3A10.1007%2Fs10995-010-0717-1/MediaObjects/10995_2010_717_Fig1_HTML.gif
Fig. 1

a Prevalence of chronic diseases (CD) and/or related risk factors (RF)b by Federal Poverty Level (FPL), among women who delivered a live birth in 5 states, PRAMS 2005–2006. a The overall association between income and number of chronic diseases and related risk factors was significant at chi-square P value < 0001. b Total number of chronic diseases and related risk factors were added for women who reported: (1) preexisting diabetes (2) binge drinking (3) being obese (4) gestational diabetes (5) above the Institute of Medicine (IOM) recommendation for weight gain (6) chronic hypertension (7) pregnancy induced hypertension (8) experiencing depression always or often (9) smoked before or during pregnancy. Since data were not made available from New York and Florida on diabetes, hypertension, and postpartum depressive symptoms, they are not included in the total number of chronic diseases and related risk factor prevalence estimates

The prevalence of chronic diseases and related risk factors among low-income women were as follows: weight gain during pregnancy above IOM recommendations, 51.7%; smoked before pregnancy, 34.2%; smoked during pregnancy, 24.8%; experienced postpartum depressive symptoms, 23.3%; obese before pregnancy, 22.2%; binge drank before pregnancy, 16.5%; PIH, 5.0%; GDM, 3.3%; preexisting diabetes, 2.9%; and chronic hypertension, 0.8% (Table 3). Results from the sensitivity analysis indicated no significant difference in the prevalence of chronic disease or related risk factors among low-income women combined with women whose income was missing, compared with the prevalence of disease and related risk factors among low-income women only (data not shown).

The Association Between FPL and Chronic Diseases and Related Risk Factors

Compared to higher-income women, low-income and near-low-income women were more likely to have smoked before (low-income: aOR = 2.9, 95% CI = 2.3–3.6; near-low-income: aOR = 1.7, 95% CI = 1.4–2.0) and during pregnancy (low-income: aOR = 5.4, 95% CI = 4.1–7.1; near-low-income: aOR = 2.6, 95% CI = 2.0–3.4); and to have been obese (low-income: aOR = 1.9, 95% CI = 1.5–2.4; near-low-income: aOR = 1.8, 95% CI = 1.4–2.1): experience postpartum depressive symptoms (low-income: aOR = 2.8, 95% CI = 2.1–3.6; near-low-income: aOR = 1.6, 95% CI = 1.3–2.1) and have 3 or more chronic diseases and/or related risk factors (low-income: aOR = 2.6, 95% CI = 1.7–4.0; near-low-income: aOR = 1.8, 95% CI = 1.3–2.6). Low-income women and near-low-income women were less likely to have binge drank before pregnancy (low-income: aOR = 0.4, 95% CI = 0.3–0.5; near-low-income: aOR = 0.5, 95% CI = 0.4–0.6) than higher-income women. Low-income women were more likely to have preexisting diabetes (aOR = 2.0, 95% CI = 1.1–3.7) and near-low-income women were more likely to have chronic hypertension (aOR = 2.6, 95% CI = 1.4–4.9) than higher-income women (Table 4).
Table 4

The association between Federal Poverty Level (FPL) and chronic disease risk factors and conditions among women who delivered a live birth in 7 states, PRAMS 2005–2006

 

Low-incomea (0–100% FPL) (n = 5,621)

Near-low-incomea (101–250% FPL) (n = 4,340)

ORb

95% CIc

ORb

95% CIc

Prepregnancy

Preexisting diabetes*

 Yes

2.0

1.1–3.7

1.5

0.8–2.7

Chronic hypertension*

    

 Yes

1.2

0.6–2.3

2.6

1.4–4.9

Smoking 3 months before pregnancy

 Yes

2.9

2.3–3.6

1.7

1.4–2.0)

Binge drinking 3 months before pregnancy**

 Binge drinker

0.4

0.3–0.5

0.5

0.4–0.6

 Non binge drinkers

0.4

0.3–0.4

0.5

0.4–0.6

 Non drinkers

Ref

Ref

Body Mass Index (BMI)

 Underweight (<18.5 kg/m2)

1.8

1.2–2.7

1.5

1.1–2.2

 Normal (18.5–24.9 kg/m2)

Ref

Ref

 Overweight (25.0–29.9 kg/m2)

1.4

1.1–1.7

1.4

1.1–1.6

 Obese (≥30.0 kg/m2)

1.9

1.5–2.4

1.8

1.4–2.1

During pregnancy

Gestational diabetes*

 Yes

1.1

0.7–1.8

1.5

1.0–2.3

Pregnancy induced hypertension*

 Yes

1.3

0.8–2.1

1.1

0.8–1.7

Smoking at any time during pregnancy

 Yes

5.4

4.1–7.1

2.6

2.0–3.4

Weight gain***

 Below IOM recommendation

1.2

0.9–1.6

1.4

1.1–1.7

 Within IOM recommendation

Ref

Ref

 Above IOM recommendation

1.0

0.8–1.3

0.9

0.8–1.1

Postpartum Conditions

    

Depressive symptoms*

    

 Always/often

2.8

2.1–3.6

1.6

1.3–2.1

 Sometimes/rarely or never

Ref

Ref

Total number of chronic diseases and risk factors

0

Ref

Ref

1

1.1

0.7–1.6

1.1

0.8–1.5

2

1.8

1.2–2.8

1.5

1.1–2.0

3+

2.6

1.7–4.0

1.8

1.3–2.6

Adjusted for maternal age, race/ethnicity, and education

Data are weighted to represent all live births in 7 states (Florida, Nebraska, New York, Ohio, South Carolina, Washington, Vermont)

* Preexisting diabetes, gestational diabetes, chronic hypertension, and pregnancy induced hypertension data not available from New York, and postpartum depressive symptoms data not available from Florida

** Binge drinkers included women who indicated drinking 5 or more drinks in 1 sitting prior to pregnancy, non binge drinkers indicated drinking during the last 2 years and either did not binge drink or drink at all prior to pregnancy

*** Based on the 2009 Institute of Medicine (IOM) recommendations for women’s weight gain for a singleton, term pregnancy

aAs compared to higher-income level (>250%)

bOR, odds ratio

cCI, confidence interval

Discussion

Our study found that among women in 7 states who delivered a live infant in 2005 and 2006, one-third were living at or below the federal poverty level. Almost one-third of low-income women reported having three or more selected chronic diseases or related risk factors, compared with approximately one-sixth of higher-income women, and almost half of low-income women reported being uninsured before pregnancy compared with 5% of higher-income women. A major strength of our study is its contribution to the existing literature on the prevalence of several chronic disease conditions and related risk factors among low-income women of reproductive age. A few previous studies have examined the prevalence, specifically, of one condition and/or risk factor among low-income women of reproductive age [11, 12]. Kim et al. [11] found women who were enrolled in the federal Women, Infants, and Children (WIC) program had higher rates of obesity, compared with women not enrolled. Tong et al. [12] found low-income women had higher rates of cigarette smoking before, during, or after pregnancy than higher-income women. Consistent with our study findings, Ahluwalia and colleagues (2005), [13], found less educated women in their reproductive years had higher rates of obesity and cigarette smoking, compared with women with higher levels of education.

Smoking

In the United States, almost 174,000 deaths among females of all ages are attributable to smoking annually [14]. The U.S. Preventive Task Force (USPTF) recommends that all adults be screened for smoking and that effective cessation interventions, such as counseling and cessation medications, be offered to aid smokers in their quit attempts [15]. Our findings indicate that one-third of low-income women in our study smoked prior to pregnancy. Increasing permanent smoking cessation during the childbearing years would significantly reduce female smoking-related deaths and long-term morbidity. If smoking cessation can be achieved before a woman becomes pregnant, many smoking-related maternal and infant adverse outcomes could also be avoided [16]. In addition, smoking cessation before a woman becomes pregnant results in the greatest benefit to the offspring.

Postpartum Depressive Symptoms

This study found that almost one-fourth of low-income women reported postpartum depressive symptoms, and it is likely that a proportion of these women would meet the criteria for clinical depression [17]. Depression can recur and these women may be at risk for future episodes of depression. Additionally, women with depression can have difficulty performing daily activities, bonding to their infants, or maintaining a positive relationship with their spouse [1820]. Routine screening for depression during reproductive health care visits is supported by the USPTF, but only if systems are in place to ensure accurate diagnosis, effective treatment, and follow-up [21]. The availability of publicly funded mental health services is often limited. Therefore, while depression may be common among women accessing reproductive health care services, screening may not be appropriate if affordable and effective services are not available [22, 23].

Obesity and Gestational Weight Gain

Obesity, observed in one-fifth of low-income women in our study, increases the risk for chronic diseases such as coronary heart disease; type 2 diabetes; certain cancers, such as endometrial, breast, and colon, and osteoarthritis, as well as early death [8]. We found that almost half of the women in our sample gained excess weight during pregnancy. While excess weight gain during pregnancy is not typically viewed as a risk factor for chronic disease, it can increase the risk of future obesity [24, 25] and the risk of developing complications in current and future pregnancies, such as GDM and pre-eclampsia [9, 1628]. Intensive lifestyle interventions can be effective in reducing weight and increasing exercise among postpartum women and women of reproductive age, but these interventions may not be available to low-income women due to cost [2931].

Diabetes

Preexisting diabetes can cause poor pregnancy outcomes if glycemic control is not achieved before conception. While the preexisting diabetes prevalence among low-income women in this study was low (<3%), it was almost twice as high in low-income women than in high-income women, and this remained statistically significant after adjustment for demographic factors. Poor glucose control can lead to long-term maternal health complications, including cardiovascular disease, retinopathy, and nephropathy. Of particular concern is the challenge of glucose control for uninsured women with diabetes. The American Diabetes Association (ADA) currently recommends screening for type 2 diabetes in adults with select characteristics such as being overweight or obese, having one or more risk factors (e.g. physical inactivity, first-degree relative with diabetes), having hypertension, high cholesterol, polycystic ovarian syndrome, impaired glucose tolerance on prior testing, as well as a prior history of GDM, delivery of a macrosomic infant, or cardiovascular disease [32].

We found that about 3% of low-income women experienced GDM during pregnancy. Women with a history of GDM are at high risk for developing chronic diabetes in the future. However, randomized clinical trials have documented that moderate weight loss with increased physical activity and dietary modifications are effective in delaying or preventing the development of type 2 diabetes in individuals at high risk [33]. Women with a history of GDM are excellent candidates for these types of interventions. Most major organizations recommend routine screening for diabetes in this population along with lifestyle change [34].

Hypertension

Among the chronic diseases and related risk factors examined in this study, chronic hypertension had a low prevalence among low-income women (approximately 1%) and near-low-income women (approximately 2%); near-low-income women were more likely to have chronic hypertension as compared to higher-income women in our multivariate analysis. Chronic hypertension is associated with an increased risk of heart disease, kidney damage, stroke, and heart attack. Untreated and unmonitored, severe chronic hypertension can also lead to adverse effects on maternal and fetal health during pregnancy [35, 36]. The Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure recommends routinely screening for hypertension by measuring blood pressure (BP) at least once every 2 years among adults with normal blood pressure and every year among adults with higher blood pressure [37].

We found that 5% of women had pregnancy induced hypertension. Women with a history of PIH are at risk for future chronic disease such as chronic hypertension, cardiovascular disease, metabolic syndrome, and for developing PIH in subsequent pregnancies [3840]. Women with PIH may benefit from follow-up that includes blood pressure monitoring and lifestyle interventions to promote weight loss such as diet and exercise modifications [39]; however, more research is needed on the effectiveness of such interventions [41].

Alcohol

Of all the conditions and risk factors explored, binge drinking was the only factor that was significantly more prevalent among women with higher-income than among women with low-income. Recent research in alcohol use supports these findings [42]. Binge drinking is associated with hypertension, cancer, cirrhosis, acute myocardial infarction, and poor control of diabetes [43, 44], and can lead to alcohol dependency later in life [4547]. Binge drinking among women of reproductive age is of concern because many pregnancies are unplanned, and women often do not know they are pregnant until several weeks or more after conception. They may unknowingly expose their fetus to the adverse effects of alcohol early in the pregnancy, during the critical period of fetal organ development [48]. The USPSTF recommends screening for alcohol misuse and behavioral counseling interventions in primary care settings however, certain high-risk groups (e.g. smokers, young adults) may benefit the most from frequent screening. The USPSTF also recommends that all pregnant women and women contemplating pregnancy should be informed of the harmful effects of alcohol on the fetus and that there is no known safe level of alcohol consumption during pregnancy (www.ahrq.gov/clinic/3rdUSpstf/alcohol/alcomisrs.htm). Public health efforts may want to especially target higher-income women of reproductive-aged with the recommended screenings and education.

Limitations

This study has limitations. First, the prevalence of chronic diseases and related risk factors are based on self-reports or on birth certificates and they are likely to be underestimated [49, 50]. In addition, the income question on the PRAMS questionnaire is reported in categorical ranges. Our calculation to create the FPL categories may have led to some misclassification which would underestimate differences in prevalence among the income groups. However, based on the results of our sensitivity analysis, the impact of missing data on income (8%) is not likely to have affected the results of the study. Finally, these findings are representative of all live births from the 7 states included in our analyses, and not to the entire U.S.

Conclusions

In conclusion, we found that low-income women of reproductive age have substantial health care needs related to chronic disease. For many women, their entry point into the health care setting is the family planning clinic; as many as 6 in 10 women who receive care at a family planning clinic consider it their usual source of care [4, 5]. Expanding services, however, could pose significant challenges and require careful planning [51]. One intermediate approach is to first ensure that current screening practices outlined in program guidelines are being performed consistently and with appropriate referrals. Increasing services for these women in publicly funded family planning clinics has the potential to reduce disparities in pregnancy and long-term outcomes among low-income women.

Appendix: Weekly maternal weight gain ranges for a normal weight woman

The numbers calculated below begin with the IOM recommended total weight gain (25–35 lbs) for a term pregnancy for a normal weight woman (BMI 18.5–24.9 kg/m2) and then subtract the IOM recommended average weekly gain in the 2nd and 3rd trimester (1.0 lbs) for each week below 37 weeks

Week

Lower end (lb)

Upper end (lb)

37–44

25.0

35.0

36

24.0

34.0

35

23.0

33.0

34

22.0

32.0

33

21.0

31.0

32

20.0

30.0

31

19.0

29.0

30

18.0

28.0

29

17.0

27.0

28

16.0

26.0

27

15.0

25.0

26

14.0

24.0

25

13.0

23.0

24

12.0

22.0

23

11.0

21.0

22

10.0

20.0

21

9.0

19.0

20

8.0

18.0

19

7.0

17.0

18

6.0

16.0

17

5.0

15.0

16

4.0

14.0

15

3.0

13.0

14

2.0

12.0

13

1.0

11.0

Similar weekly weight gain ranges were also developed for underweight women (BMI < 18.5 kg/m2, IOM recommended total gain 28–40 lbs with a mean weekly gain of 1.0 lbs), overweight women (BMI 25.0–29.9 kg/m2, IOM recommended total gain 15–25 lbs with a mean weekly gain of 0.6 lbs), and obese women (BMI ≥30.0 kg/m2, IOM recommended total gain 11–20 lbs with a mean weekly gain of 0.5 lbs)

Footnotes
1

Gestational diabetes and pregnancy induced hypertension are classically defined as conditions which are first diagnosed during pregnancy and which resolve after pregnancy. Women classified with these conditions may also have chronic forms of the condition, either due to lack of diagnosis prior to pregnancy or lack of resolution of the condition after pregnancy.

 

Acknowledgments

The authors would like to acknowledge Kim Burley for statistical programming consultation and state PRAMS coordinators (Marie Bailey, Florida; Brenda Coufal, Nebraska; Anne Radigan-Garcia, New York; Carrie Hornbeck, Ohio; Michael Smith, South Carolina; John Gauthier, Vermont; Linda Lohdefinck, Washington) for assisting with the collection of additional data as well as allowing use of their respective PRAMS data.

Disclaimer

The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

Copyright information

© Springer Science+Business Media, LLC (outside the USA) 2010