Perceptions and Behaviors Related to Contraceptive Use in the Postpartum Period Among Women With Pregestational Diabetes Mellitus

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Perceptions and Behaviors Related to Contraceptive Use in the Postpartum Period Among Women With Pregestational Diabetes Mellitus

Q1

Laura E. Britton, Diane C. Berry, Jamie L. Crandell, Jada L. Brooks, and Amy G. Bryant

Q17

Correspondence Laura E. Britton, Columbia University School of Nursing, 560 W 168th Street, New York, NY 10032. [email protected]. edu

ABSTRACT

Keywords contraception diabetes mellitus postpartum period preconception care

Participants: Fifty-five women who were 18 years or older with pregestational Type 1 or Type 2 diabetes mellitus.

Objective: To describe perceptions and behaviors related to contraception and preconception care and to test the association between these perceptions and contraceptive use in the postpartum period among women with pregestational diabetes mellitus. Design: Cross-sectional, descriptive survey. Setting: Three high-risk obstetric clinics in the Southeastern United States.

Methods: Between 4 and 8 weeks after birth, we used investigator-developed items and psychometrically validated scales to measure participants’ perceptions and behaviors related to contraception and preconception care. We dichotomized use of contraception in the postpartum period as procedure/prescription or nonprescription/no method. We used multiple logistic regression to test the hypothesis that perceptions are associated with contraceptive use. Results: When data were collected 4 to 8 weeks after birth, almost half (49%, n ¼ 27) of the participants had resumed sexual activity; however, most (95%, n ¼ 52) did not want another pregnancy in the next 18 months. Fifty-six percent (n ¼ 31) of participants used procedure/prescription contraception, and 44% (n ¼ 24) used nonprescription/no method. Those who perceived contraception use and preconception care to be beneficial were more likely to use procedure/ prescription contraception (adjusted odds ratio ¼ 1.52; 95% confidence interval [1.07, 2.17]). Conclusion: When caring for women in the postpartum period, providers should be mindful that women’s perceptions of the benefits of contraception and preconception care may have implications for whether their use aligns with their reproductive goals and optimizes outcomes for future pregnancies.

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2020. https://doi.org/10.1016/j.jogn.2019.12.002 Accepted December 2019

Laura E. Britton, PhD, RN, is a postdoctoral fellow in the School of Nursing, Columbia University, New York, NY. Diane C. Berry, ANP-BC, FAANP, FAAN, is a Jane Sox Monroe Distinguished Professor in the School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC. (Continued)

The authors report no conflicts of interest or relevant financial relationships.

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he incidence of pregestational diabetes (henceforth referred to as diabetes in this article) during pregnancy is rising in the United States (Admon et al., 2017; Bardenheier et al., 2015; Correa, Bardenheier, Elixhauser, Geiss, & Gregg, 2014). Between 2000 and 2010, the prevalence of diabetes increased from 0.65 to 0.89 per 100 births (Bardenheier et al., 2015). When blood glucose is elevated during pregnancy, women with Type 1 diabetes mellitus (T1DM) or Type 2 diabetes mellitus (T2DM) experience greater rates of adverse outcomes, including perinatal loss and fetuses with congenital malformations (Feig et al., 2014; Timar et al., 2014). The American Diabetes Association

(2019) recommended preconception care, including the use of contraceptives, until women with diabetes are ready for pregnancy, ideally with glycated hemoglobin (A1C) levels lower than 6.5% to minimize the risks of obstetric complications. An estimated $767 million in direct medical costs and $3.6 billion in lost productivity could be saved by preconception care for all women diagnosed with diabetes (Peterson et al., 2015; Wahabi, Alzeidan, Bawazeer, Alansari, & Esmaeil, 2010). However, among women surveyed in 10 states for the 2009 to 2010 Pregnancy Risk Assessment Monitoring System, only 53% of women with diabetes reported that they obtained preconception care when they were

ª 2020 AWHONN, the Association of Women’s Health, Obstetric and Neonatal Nurses. Published by Elsevier Inc. All rights reserved.

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Postpartum Contraceptive Use Among Women With Diabetes

After birth, effective contraception may be underused by women with pregestational diabetes, a condition that elevates the risk of obstetric complications.

asked “Before you got pregnant with your new baby, did you talk with a doctor, nurse, or other health care worker to prepare for a healthy pregnancy and baby?” (Kachoria & Oza-Frank, 2014). During the postpartum period, contraception can prevent unintended pregnancy and support healthy pregnancy intervals while women with diabetes can work to establish euglycemia (Thiel de Bocanegra, Chang, Howell, & Darney, 2014). In non–population-based samples, uptake of contraception after childbirth by women with diabetes ranged from 52% (Schwarz et al., 2017) to 77% (Perritt, Burke, Jamshidli, Wang, & Fox, 2013). A better understanding of the behaviors and perceptions that can affect unintended pregnancy risk, including when women resume sexual activity after childbirth or whether they view contraception favorably, can also support efforts to achieve high-quality, patient-centered maternity care.

Jamie L. Crandell, PhD, is a research assistant professor in the School of Nursing and Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC. Jada L. Brooks, PhD, MSPH, RN, is an assistant professor in the School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC. Amy G. Bryant, MD, MSCR, is an associate professor in the School of Medicine, Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, NC.

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To identify potentially modifiable targets for nursing interventions, we conceptualized contraceptive use in the postpartum period as a health behavior that could be influenced by three constructs from Pender’s Revised Health Promotion Model. Pender (2011, p. 4) defined perceived benefits of action as “perceptions of the positive or reinforcing consequences of undertaking a health behavior”; perceived barriers to action as “perceptions of the blocks, hurdles, and personal costs of undertaking a health behavior”; and perceived self-efficacy as “judgment of personal capability to organize and execute a particular health behavior; self-confidence in performing the health behavior successfully.” In this study, we collectively refer to Pender’s three constructs as perceptions. Among women with diabetes who have not recently given birth, high levels of selfefficacy about the use of contraception and obtaining preconception care were associated with their perceived usefulness (Grady & Geller, 2016) and care-seeking behavior (Komiti et al., 2014). In qualitative research studies, women with diabetes who perceived limited benefits or substantial barriers to obtaining contraception or preconception care were inclined to obtain neither (Charron-Prochownik et al., 2015;

Chuang, Velott, & Weisman, 2010; Earle et al., 2017; McCorry, Hughes, Spence, Holmes, & Harper, 2012; Murphy et al., 2010; O’Higgins, Mcguire, Mustafa, & Dunne, 2014; Shawe, Smith, & Stephenson, 2011). Therefore, we conducted a survey of women with diabetes in the postpartum period to describe perceptions and behaviors related to contraception and preconception care and to test the association between these perceptions and contraceptive use in the postpartum period among women with diabetes.

Methods Design We used a cross-sectional, descriptive survey to measure perceptions and behaviors related to contraception and preconception care. We obtained informed consent from all participants. The Institutional Review Board of the University of North Carolina at Chapel Hill approved all study procedures.

Participants and Setting We surveyed adult women who had diabetes before recent pregnancies. We used the following inclusion criteria for participation: age 18 years or older, diagnosis of T1DM or T2DM before pregnancy, and consent to complete a survey in English between 4 and 8 weeks after birth. Exclusion criteria were fetal demise, newborn with major malformation, or instructions in the electronic health record or from a provider indicating that the woman should not be contacted. Participant recruitment and study procedures occurred at three high-risk obstetric clinics in a public not-for-profit integrated health care system that is associated with a Southeastern academic medical center. These clinics provide care regardless of insurance status. Nurse practitioners and obstetricians, including maternal– fetal medicine specialists, provide care during and after pregnancy. Site partners estimated that they served approximately 150 women who met eligibility criteria in the previous year. We conducted a power analysis to determine our target enrollment. With the assumption, as reported by Schwarz, Maselli, and Gonzales (2006), that approximately 30% of the participants would use procedure/prescription contra- Q2 ception and 70% would use nonprescription/ none, a total of 90 participants would allow for 80% power to detect a medium to large standardized mean difference of Cohen’s d ¼ .65

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Britton, L. E., Berry, D. C., Crandell, J. L., Brooks, J. L., and Bryant, A. G.

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between the two groups in a two-tailed t test with a significance level of .05.

Procedures

Q3

We identified potentially eligible women in the system-level electronic health record that integrates outpatient and inpatient care. We made the initial contact in person (at the clinic) or remotely (by phone or e-mail) between 37 weeks gestation and 8 weeks after birth to describe the study objectives and procedures. When a woman expressed interest, we confirmed eligibility, described the study in more detail, answered questions, and confirmed preferred communication mode (phone or e-mail). We obtained informed consent in person or through an online informed consent form on a secure Qualtrics platform; study personnel were available for questions. On site, participants could complete the survey on a study iPad (Apple, Cupertino, CA) or on paper, or they could follow a link to complete the survey on the Qualtrics platform from their own devices. Participants could also provide consent remotely via a hyperlink. We confirmed the date of birth in the electronic health record to send links to the survey between 4 and 8 weeks after birth. We gave participants who completed the survey $20.

Measures The survey contained 35 questions, including 13 questions about participant characteristics and 22 items/scales (general perceptions and behaviors; pregnancy planning; perceived selfefficacy, barriers, and benefits of contraception and preconception care; and contraceptive use). There were also two free-text fields where participants could provide qualitative responses. We used investigator-developed items unless indicated otherwise.

Q4

Participant characteristics. Participants provided demographic data, including age, race, ethnicity, educational attainment, religion, parity, and health insurance status. Diabetes characteristics included type and participant age at diagnosis from which we calculated the duration. General perceptions and behaviors. We asked participants whether they resumed sexual activity since the birth and, if so, when and how often. We asked them about their desires for future childbearing and the timing of pregnancy using wording modeled on the National Survey of Family Growth (Centers for Disease Control and

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Prevention, 2016). Participants answered a series of single-item questions about perceptions of contraception and preconception care, including whether (a) diabetes influenced their choice of contraception, (b) diabetes caused complications in their recent pregnancies, (c) contraception was safe for women with diabetes, (d) contraception was effective for women with diabetes, (e) women with diabetes needed contraception as much as women without diabetes, and (f) diabetes made it harder for women with diabetes to get pregnant. Items were analyzed individually. Participants could indicate agree, disagree, or that they did not know. In an opentext field at the end of the survey, we asked the participants if they wanted researchers to know anything else about their experiences.

Pregnancy planning. We used the London Measure of Unplanned Pregnancy (LMUP) scale to measure the degree to which the recent pregnancy was planned (Barrett, Smith & Wellings, 2004). There is an ongoing debate about what affective and cognitive constructs constitute pregnancy intention (Aiken, Borrero, Callegari, & Dehlendorf, 2016; Kavanaugh & Schwarz, 2009; Santelli, Lindberg, Orr, Finer, & Speizer, 2009). Diabetes can further complicate women’s feelings about trying to become pregnant and using preconception care (McCorry et al., 2012; Murphy et al., 2010; Paiva, 2016). The LMUP elicits multiple dimensions of pregnancy intentions through six items scored 0 to 2; the possible total scores range from 0 to 12. The authors of the LMUP noted that the scale should be used as a continuous variable because cutoffs for a categoric variable had not been adequately validated (G. Barrett, personal communication, February 7, 2017). Greater values indicate that the recent pregnancy was more planned. Initially, the authors of the LMUP developed the scale in Britain with women who were pregnant or recently pregnant and recruited participants at antenatal, abortion, and general practitioner clinics. The Cronbach’s alpha coefficient estimate of internal consistency reliability was 0.92, and other assessments of validity and reliability are described elsewhere (Barrett et al., 2004). Morof et al. (2012) made minor modifications to the LMUP to adapt the scale to the United States, and reliability and validity were evaluated as sufficient (including Cronbach’s alpha coefficient ¼ 0.78, all item-total correlations >0.2, and weighted kappa ¼ 0.72 for the English language version).

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Postpartum Contraceptive Use Among Women With Diabetes

In our sample, the standardized Cronbach’s alpha coefficient for the LMUP was 0.88 (n ¼ 54). Perceived self-efficacy, barriers, and benefits of contraception and preconception care. We measured the perception of selfefficacy, barriers, and benefits of contraception and preconception care with psychometrically validated scales from the theory-based Reproductive Health Attitudes and Behaviors (RHAB) questionnaire designed for use with adolescent women with T1DM (Charron-Prochownik, Wang, Sereika, Kim, & Janz, 2006). The RHAB Benefits scale contains four items with total scores that range from 4 to 20, the RHAB Barriers scale contains five items with total scores that range from 5 to 25, and the RHAB SelfEfficacy scale contains six items with scores that range from 0 to 60 (Charron-Prochownik, et al., 2006). A higher score indicates a greater endorsement of the three scales’ concepts. On the RHAB Barrier scale, participants could indicate that an item is not applicable, in which case we used mean imputation to calculate the final score, an analytic approach that the creator of the RHAB approved (D. Charron-Prochownik, personal communication, May 7, 2019). We noted that several items on the RHAB scales reference preconception care, which was defined as “achieving normal blood sugars, obtaining preconception counseling, and using effective birth control” (Charron-Prochownik et al., 2006, p. 211). In the original study, Cronbach’s alpha coefficient estimates of internal consistency were 0.65, 0.72, and 0.65 for the RHAB Benefits scale, the RHAB Barriers scale, and the RHAB Self-Efficacy scale, respectively (Charron-Prochownik et al., 2006). In our sample, the standardized Cronbach’s alpha coefficients were 0.55 (n ¼ 54) for the RHAB Benefits scale, 0.80 (n ¼ 52) for the RHAB Barriers scale, and 0.81 (n ¼ 53) for the RHAB SelfEfficacy scale. Use of contraceptives. We queried which contraceptive method(s), if any, participants were using. The procedure/prescription methods included female sterilization (tubal ligation or tubes tied or blocked); male sterilization (vasectomy); intrauterine device without hormones (Paragard); intrauterine device with hormones (Mirena, Skyla, or Liletta); etonogestrel implant (Norplant, Implanon, or Nexplanon); birth control pills, patch, or ring; the Depo-Provera injection;

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diaphragms; or emergency contraception. The Q5 nonprescription methods included male or female condoms; withdrawal; vaginal sponge; contraceptive film, suppository, or cream; and lactational amenorrhea. Nonusers could provide multiple reasons for using no method. For hypothesis testing, participants were categorized into two groups: prescription/procedure or nonprescription/no method. Participants who selected more than one method were categorized according to the most effective method selected. Nonprescription and no method were categorized together because they are less effective than procedure/prescription methods (except for perfectly executed lactational amenorrhea, which was beyond the scope of this study) and do not require interfacing with the health care system (Hatcher et al., 2018).

Data Analysis We performed all analyses in SAS version 9.4. To describe the perceptions and behaviors related to contraception and preconception care, we provided descriptive statistics for perceptions and behaviors and tested bivariate associations with contraceptive use. For continuous variables, we reported means/standard deviations; when not approximately normally distributed, we reported medians/interquartile ranges. For categoric variables, we reported counts/percentages. When we analyzed responses to our questions about general perceptions, participants who agreed were compared with those who disagreed or did not know. To test the bivariate associations for continuous variables, we used two-sample t tests or, in the case of nonnormality, the nonparametric Wilcoxon test of association. For categoric variables, we used the c2 test or Fisher’s exact test if 25% or more of the cells contained fewer than five observations. To test the associations among perceptions and contraceptive use in the postpartum period, we built three models for procedure/prescription contraceptive use with multiple logistic regression using scores for the RHAB Benefits scale, the RHAB Barriers scale, and the RHAB Self-Efficacy scale as the predictors. We tested the hypothesis that contraceptive use was associated with perceived self-efficacy, barriers, and benefits of contraception and preconception care. As determined a priori, we controlled for demographic characteristics (age, race and ethnicity, educational attainment, insurance, and type of diabetes), whether sexual activity had been resumed after birth, and LMUP score. We also planned to control

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Unable to contact (n = 10) Perinatal loss or serious malformaon (n = 11) Instructed not to contact by nurse or medical records (n = 3)

Idenfied as eligible (n = 120)

Did not respond (n = 29) Declined to parcipate (n = 1) Expressed interest but did not sign consent before 8 weeks postpartum (n = 5)

Contacted (n = 96)

Consented (n = 61)

Did not complete survey (n = 6)

Parcipants included in final sample (n = 55) Figure 1. A flow diagram of participant recruitment. We initially had institutional review board approval to approach women in person, but this was not possible when they did not attend their postpartum appointments. After we obtained approval to contact women by phone or e-mail, we were still unable to contact 29 women who did not respond to e-mail, texts, or calls. We also did not contact women if the nurses providing their care instructed us not to approach them or if similar instructions were included in the electronic health record.

for any study variables that showed a bivariate association with contraceptive use at the 0.05 significance level. Because of our sample size, we collapsed race and ethnicity, education, and insurance into two-level categories for hypothesis testing. We compared non-Hispanic White participants with participants of all other races and ethnicities based on the data about racial and ethnic disparities in diabetes outcomes and quality of care (Ali, McKeever Bullard, Imperatore, Barker, & Gregg, 2012).

Results Participant Characteristics Between June 2017 and September 2018, we identified 120 women in the electronic health record who met the eligibility criteria (see Figure 1). We approached or contacted 96 women, of whom 61 agreed to participate. We did not meet our a priori sample size estimate. Fifty-five women completed the survey at a median of 6 weeks postpartum. Participants ranged from 21 to 44 years old, with a median age of 32 years (see

Table 1). Most participants were multiparous (58%, n ¼ 32), non-Catholic Christians (72%, n ¼ 40) and had completed some college or vocational training (75%, n ¼ 41). Most participants were nonHispanic Black (35%, n ¼ 19), non-Hispanic White (33%, n ¼ 18), or Hispanic (24%, n ¼ 14). Most participants had insurance (81%, n ¼ 45). Diabetes was diagnosed between ages 5 and 44 years, with a median age of 26 years. The median duration since diagnosis was 7 years (range, < 1–31 years). Almost three quarters (73%, n ¼ 40) of the participants had T2DM, and the remainder (27%, n ¼ 15) had T1DM. Demographic characteristics did not significantly vary by diabetes type, except that participants with T1DM were more likely to be non-Hispanic White (p ¼ .02). Diabetes characteristics varied by type. Participants with T1DM were diagnosed younger than those with T2DM (p < .0001). Participants received T1DM diagnosis between the ages of 5 and 21 years, whereas participants with T2DM were diagnosed between the ages of 13 and 44 years. Participants with T1DM had

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Postpartum Contraceptive Use Among Women With Diabetes

Table 1: Participant Characteristics (N [ 55)

Table 2: Perceptions and Behaviors of Women With Pregestational Diabetes in the Postpartum Period (N [ 55)

Categoric Variable

n

Percentage

First birth

23

41.8

Race and ethnicity Hispanic, any race

14

25.5

Non-Hispanic, Asian

2

3.6

Non-Hispanic, Black

19

34.5

2

3.6

Non-Hispanic, other or

Categoric Variable

n

Percentage

Has had sex since the childbirth

27

49.1

Frequency of sex was

22

81.5

once a week or lessa Want to be pregnant again ever

more than one Non-Hispanic, White

18

Christian, not Catholic

18

32.7

Yes

15

27.3

22

40.0

Within 18 months

3

20.0

18 months–2 years

2

13.3

2–5 years

9

60.0

Uncertain

32.7

Wants to be pregnant again

Religion Catholic

No

10

18.2

40

72.7

5

9.1

Other or none

b

More than 5 years

Educational attainment Less than high school

2

43.6

High school graduate

12

21.8

Some college or

17

30.9

Thinks about diabetes when

1

6.7

20

36.4

29

52.7

9

16.4

4

7.3

2

3.6

21

38.2

9

16.4

making decisions about

vocational training College graduate or more

birth control Believes diabetes caused complications/problems

24

43.6

Private insurance

33

60.0

Medicaid

12

21.8

None/don’t know

10

18.2

Health insurance

in index pregnancy Believes birth control is less safe for women with diabetes Believes birth control is less effective for women with diabetes Believes women with diabetes

Type of diabetes Type 1

15

27.3

Type 2

40

72.7

need birth control less than other women Believes diabetes makes it harder for women to get pregnant

Interquartile Range

Diabetes management part

Age

32

28–37

of preconception care for

Age at diagnosis

26

16–31

Years since diagnosis

7

2–13

Continuous Variable

Median

index pregnancy Interquartile Continuous Variable Weeks after childbirth when

diabetes longer than those with T2DM, with a median of 18 years versus 3 years (p < .001).

Description of Perceptions and Behaviors Related to Contraception and Preconception Care Q6

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General perceptions and behaviors. In Table 2, we report univariate findings of

Median

Range

5

4–6

9

6–11

sex resumed, mediana London Measure of Unintended Pregnancy, median a

Among the 27 women who had sex since the birth. bAmong the 15 women who wanted to become pregnant again. For hypothesis testing, women who wanted pregnancies within 2 years compared with women who wanted pregnancies in more than 2 years.

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perceptions and behaviors in the postpartum period. Forty-nine percent of participants had resumed sexual intercourse between 4 and 8 weeks after childbirth (n ¼ 27). Resumption occurred between 1 and 7 weeks, with a median of 5 weeks, and frequency was once per week or less for 80% (n ¼ 22) of sexually active participants. Most participants did not want another child (27%, n ¼ 15) or were uncertain (40%, n ¼ 22). Of the 15 participants who did want another child, most (n ¼ 9) desired to conceive within 2 to 5 years.

Q7

Most participants reported that they did not think about diabetes when making decisions about birth control (64%, n ¼ 35) and that they believed diabetes caused complications in their most recent pregnancy (53%, n ¼ 29). Participants who believed they experienced diabetes-related complications were no more likely to think about diabetes when making contraceptive decisions than participants who experienced no complications (p ¼ .79). Few participants thought that birth control was less safe (16%, n ¼ 9) or less effective (7%, n ¼ 4) for women with diabetes or that women with diabetes need birth control less than women without (4%, n ¼ 2). However, 38% (n ¼ 21) thought diabetes makes it harder for women to get pregnant. Participants were given an open-text field into which they could share any final thoughts. One participant shared the following: “Great precounseling [sic] and care before pregnancy contributes to a great pregnancy when diabetic.” Another participant wrote, “Insulin and dieting played a major part in preventing my baby from getting any bigger than he was at birth.” Another described how difficult it was for her to manage her condition financially as follows: Not having money for my insulin makes everything harder when it’s $200 a vile [sic] for the cheapest one. It’s ridiculous I can’t take care of myself. Not everyone has a family to help them and sometimes things get really hard but I’d do anything for my baby. I try my best everyday [sic] to keep her healthy. Two participants became pregnant unexpectedly when starting metformin and losing weight; in contrast, another participant had an unplanned pregnancy at a particularly unhealthy time, “Unfortunately, when I did get pregnant I was in one of my health slumps in which I was not really

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Most participants with pregestational diabetes used contraception after birth.

watching what I was eating and ultimately neglecting my diabetes. This pregnancy was very much unexpected.” Pregnancy planning. The median LMUP score was 9, which indicated that pregnancies were typically planned; nonetheless, 44% (n ¼ 24) of participants responded that they did nothing when asked “Before you became pregnant, did you do anything to improve your health in preparation for pregnancy?” Among those who reported preparations, the most common behavior was to take folic acid or prenatal vitamins (33%, n ¼18). In an open-text field, participants indicated that they pursued general wellness (e.g., “decreased stress as much as possible”), sought health care (e.g., “saw an endocrinologist for my Type 2 diabetes to discuss getting pregnant again”), and improved diabetes control (e.g., “get A1C as low as possible”). Among the 9 (16%) participants who described improving diabetes control before pregnancy, this preparation was more common among those with T1DM (n ¼ 6) than T2DM (n ¼ 3, p ¼ .01). Perceived self-efficacy, barriers, and benefits of contraception and preconception care. Participants generally endorsed high perceived self-efficacy (median score of 50 out of 60), low perceived barriers (median score of 5 out of 25), and high perceived benefits (median score of 16 out of 20) with regard to contraception and preconception care (see Table 3). None of these scores were normally distributed. Use of contraceptives. Fifty-six percent of the participants (n ¼ 31) reported that they used procedure/prescription contraception; hormonal intrauterine devices and pills were the most common methods (see Table 4). Only 11 participants (20%) reported use of nonprescription methods. Among participants who used contraceptives, two said they used contraception “sometimes.” Twenty-four percent (n ¼ 13) reported that they used no contraception since giving birth. Reasons for nonuse included desires to get pregnant, chooses not to use contraceptives, husband or partner does not support contraceptive use, fears potential side effects, and plans to start a contraceptive method.

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Postpartum Contraceptive Use Among Women With Diabetes

Providers should be aware that use of contraceptives in the postpartum period is more likely when women with pregestational diabetes view contraception and preconception care as beneficial.

Bivariate findings. No participant characteristics (see Table 1) or perceptions or behaviors (see Table 2) had a significant bivariate association with procedure/prescription contraceptive use. There was no difference in contraceptive use based on how soon after childbirth participants took the survey (p ¼ .22). Participants who used procedure/ prescription contraception had significantly higher mean RHAB Benefits scores than those who used nonprescription/no contraception (p ¼ .01; see Table 3). The mean scores for RHAB Barriers and RHAB Self-Efficacy were not significantly different between participants who did and did not use procedure/prescription contraceptives.

Associations Among Perceptions and Contraceptive Use in the Postpartum Period In the multiple logistic regression models constructed to evaluate associations, we enhanced comparability by reporting the change of log odds of using procedure/prescription contraception for a one-half standard deviation increase in each independent variable because the RHAB scales had different ranges. In the unadjusted logistic model, for every additional half of a standard deviation increase in RHAB Benefit score, the odds of using procedure/ prescription contraception increased by 1.46 (95% confidence interval [1.06, 2.01]) and then

by 1.52 (95% confidence interval [1.07, 2.17]) when we controlled for participant characteristics (see Table 3). In the models tested, one-half standard deviation increases in RHAB Barriers and RHAB Self-Efficacy were not associated with a significant increase in the odds of using procedure/prescription contraception with or without adjustments.

Discussion Guided by Pender’s Revised Health Promotion model (Pender, 2011), we provided novel findings about perceptions and behaviors in the postpartum period of the growing population of women with diabetes. More than 75% of our participants used contraception in the 4 to 8 weeks after childbirth, and most used highly effective methods. These findings are similar to the rate of postpartum contraceptive use by women with diabetes in the Maryland Pregnancy Risk Assessment Monitoring System (77%; Perritt et al., 2013) but greater than the rate in California’s Medicaid program (52%; Schwarz et al., 2017)

Participant Characteristics We identified a few notable characteristics in our participants. The median age was 32 years; therefore, many participants were considered to be of advanced maternal age (35 years and older) during their recent pregnancies or would be in future pregnancies. However, because demographic trends indicate that T2DM is emerging earlier in life, health care providers should anticipate caring for more pregnant women with diabetes in younger cohorts as well (Britton et al., 2018; Geiss et al., 2014).

Table 3: Odds Ratios for Using Procedure/Prescription Contraception Associated With Each Additional One-Half Standard Deviation Increase in Perceptions About Contraception Among Women With Pregestational Diabetes in the Postpartum Period Reproductive Health Attitudes and Behaviors Scale

Median (Interquartile Range)

Odds Ratios for Using

Adjusted Odds Ratios for

Procedure/Prescription

Using Procedure/Prescription

Contraceptionb

Contraceptionc

p Valuea

Benefits

16 (14–18)

.01

1.46 (1.06–2.01)

1.52 (1.07–2.17)

Barriers

5 (4–8)

.10

0.83 (0.63–1.11)

0.79 (0.57–1.09)

50 (44–56)

.32

1.18 (0.89–1.57)

1.13 (0.80–1.58)

Self-efficacy

a Nonparametric Wilcoxon test used to test for significant differences in the mean scores between women who used procedure/prescription contraception and women who used nonprescription/no contraception. bScaled to represent the change in odds ratio for an increase in the score equivalent to the value of one-half standard deviation for each scale from the Reproductive Health Attitudes and Behaviors questionnaire (Charron-Prochownik et al., 2006). cAdjusted for age, race, and ethnicity (dichotomized as non-Hispanic White or not), educational attainment (dichotomized as high school or less vs. some college or more), insurance (dichotomized as private vs. not), type of diabetes, whether this was their firstborn child, intendedness of index pregnancy (London Measure of Unplanned Pregnancy score), and whether they had resumed sexual activity since childbirth.

8

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Q15

841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896

Britton, L. E., Berry, D. C., Crandell, J. L., Brooks, J. L., and Bryant, A. G.

897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952

Table 4: Contraceptive Methods Used by Women With Pregestational Diabetes Between 4 and 8 Weeks After Birth (N [ 55) Contraceptive Method

n

Percentage

6

11

10

18

3

5

10

18

2

4

RESEARCH

953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008

diabetes (Murphy et al., 2010; Shawe et al., 2011). Largely, our participants did not endorse these beliefs, which underscores the importance of conducting research directly with women with diabetes in the United States to understand their concerns and needs.

Procedure/prescription Female sterilization Hormonal intrauterine device Implant Pills Injection Nonprescription/no method Withdrawal

1

2

Male condom

9

16

Lactational amenorrhea

1

2

13

24

Nothing

The use of contraceptives did not vary by race or ethnicity in our participants. These findings diverged from our previous work about nonpregnant young adult women with diabetes, among whom Hispanic women were significantly more likely to use nonprescription methods and significantly less likely to use no method (Britton et al., 2019). Nonetheless, because diabetes disproportionately affects women of color during their reproductive years (Britton et al., 2018), improving maternity care for women with diabetes may be a strategy that can contribute to greater racial and ethnic equity in reproductive health outcomes.

General Perceptions and Behaviors

Q8

Our participants resumed coitus as early as 1 week after childbirth, and almost half resumed coitus by 4 to 8 weeks postpartum. In other hospital-based samples, 43% (Sok, Sanders, Saltzman, & Turok, 2016) to 51% (Rogers, Borders, Leeman, & Albers, 2009) of women resumed sexual activity by 6 weeks after birth. Women who are not yet sexually active may benefit from the establishment of a satisfactory contraceptive method before resumption of coitus because women who are not breastfeeding may ovulate as early as 4 weeks after childbirth (Jackson & Glasier, 2011). In previous qualitative research in the United Kingdom, women with diabetes expressed the beliefs that they do not need contraception (Earle et al., 2017; Murphy et al., 2010) or that contraception is unsafe or ineffective for women with

Pregnancy Planning In our sample, most participants planned their recent pregnancies, which is similar to a finding in a study by Perritt et al. (2013) in which women with diabetes were no more likely to have mistimed or undesired pregnancies than women without medical conditions. In contrast, Chor, Rankin, Harwood, and Handler (2011) found that women with chronic illnesses may be more likely to have unplanned pregnancies than their healthier peers. The prevalence of unintended pregnancies among women with diabetes is unknown, but the occurrence is periodically noted in the qualitative research (Collier et al., 2011; Earle et al., 2017; Mersereau et al., 2011; Murphy et al., 2010; Spence, Alderice, Harper, McCance, & Holmes, 2010). For women who desire more children, the postpartum period may constitute the preconception period for a future pregnancy. Support for pregnancy planning and health optimization for women with chronic illnesses is important for their reproductive self-determination and well-being. Despite the fact that most planned their pregnancies, few of our participants tried to improve glycemic control before conception. Qualitative researchers found that women with diabetes may not fully understand the effects of diabetes on pregnancy (Chuang et al., 2010; McCorry et al., 2012; Murphy et al., 2010; O’Higgins et al., 2014), that preconception care can reduce risks (McCorry et al., 2012; Murphy et al., 2010; O’Higgins et al., 2014), or that prenatal care cannot reverse the effect of elevated blood glucose on embryogenesis (McCorry et al., 2012). Among our participants, pregnancy planning (LMUP score) was not associated with the use of contraceptives; this finding differs from the finding in one study that suggested that women with mistimed or unwanted pregnancies may be more likely to adopt highly effective contraception (Guzzo & Hayford, 2017). Our participants endorsed a variety of reasons for not using contraception (fear of side effects, partner does not support contraceptive use, and planning to start later). Nurses and other providers can tailor care to assure that women and their partners

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1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064

Postpartum Contraceptive Use Among Women With Diabetes

receive the relevant counseling needed to support their decision-making–related contraception.

Perceived Self-Efficacy, Barriers, and Benefits of Contraception and Preconception Care

Q9

Q10

10

The association between the effective use of contraceptives and the perceived benefits of contraception and preconception care was consistent with Pender’s model (2011). Women may not seek contraception or preconception care if they do not believe those actions will have any value, which is also consistent with Pender’s model (2011) and behaviors described in the qualitative literature (Chuang et al., 2010; Murphy et al., 2010; O’Higgins et al., 2014). The implications for communication are that women with diabetes may be more receptive to positive information about preconception care rather than scare tactics (Collier et al., 2011; McCorry et al., 2012). Providers face the challenge of conveying worrisome or unwelcome information because women may become frustrated with being told not to have children (Spence et al., 2010) or to delay pregnancy until their blood glucose levels are lower (Lavender et al., 2010). Women with diabetes may delay prenatal care when they fear that providers will disapprove of their pregnancies (Collier et al., 2011; Edwards, Speight, Bridgman, & Skinner, 2016; Murphy et al., 2010; Spence et al., 2010). Because our data were collected at a single time point, we do not assert that modifying perceptions about contraceptives would change contraceptive use. Future researchers should explore how promotion of the benefits of contraception and preconception care might also increase uptake and how to optimize positive health communication. Although our findings did not support a relationship between the perception of barriers or self-efficacy and the use of contraceptives, these relationships may be worth future study because other researchers suggested possible links and our sample size was small. Higher self-efficacy scores were associated with perceived usefulness of preconception counseling, birth control (Grady & Geller, 2016), and preconception careseeking behaviors (Komiti et al., 2014). The expense of diabetes supplies and medications presents barriers to optimizing blood glucose levels in the preconception period (Mersereau et al., 2011); this concern was articulated by one of our participants in an open response. Providers may alienate women by not acknowledging these barriers. Collier et al. (2011) found that participants

delayed prenatal care because they anticipated providers would criticize them for poor glycemic control when they could not afford to comply with their treatment plans. Furthermore, barriers to contraception might be particularly challenging for women to overcome as they meet the biological, psychological, and social demands of the postpartum period (Verbiest, Tully, & Stuebe, 2017).

Limitations and Recommendations for Research We sought to enroll 90 women but did not meet our target because women with diabetes in the postpartum period proved to be a hard-to-reach population. Although we engaged with site partners to assess our recruitment plan, the sites served fewer English-speaking women than projected. Recruitment increased when we obtained approval from the institutional review board to contact women by phone or e-mail; this also diminished the bias in our findings against women who did not use procedure/prescription contraception, which requires interaction with a provider. A larger sample would clarify if nonsignificant associations were related to the sample size or a true lack of association. Nonetheless, our sample size limitations did not undermine our findings of a statistically and clinically significant relationship between the perception of benefits and the use of contraceptives. Although we found it challenging to contact potentially eligible participants, our study content and format were largely received positively. Only one woman explicitly declined to participate. Although 29 women did not respond to our initial attempts at contact, we do not know if we had the correct contact information, nor do we know why some women who consented decided not to complete the survey. We were concerned about study participation being burdensome in the postpartum period, but an advantage of the online survey was that women could participate when their schedules permitted. We also had no missing data for contraceptive use and resumption of sexual activity, which suggests that these were acceptable topics for the survey. The RHAB scales and LMUP scale were not previously used with adult women with diabetes during the postpartum period and performed moderately well, although our sample size was small for good estimation of Cronbach’s alpha coefficients (Rouquette & Falissard, 2011). Our values for the Cronbach’s alpha coefficient were lower for the RHAB Benefits scale, which

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1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120

Britton, L. E., Berry, D. C., Crandell, J. L., Brooks, J. L., and Bryant, A. G.

1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176

suggests lower internal consistency in our sample than in the sample used for validation. In contrast, the values were similar for the RHAB Barriers scale and greater for the RHAB Self-Efficacy scale and the LMUP scale.

RESEARCH

1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232

Aiken, A. R., Borrero, S., Callegari, L. S., & Dehlendorf, C. (2016). Rethinking the pregnancy planning paradigm: Unintended conceptions or unrepresentative concepts? Perspectives on Sexual and Reproductive Health, 48(3), 147. https://doi.org/10. 1363/48e10316 Ali, M. K., McKeever Bullard, K., Imperatore, G., Barker, L., & Gregg, E. W. (2012). Characteristics associated with poor glycemic

To determine if certain perceptions predicted the use of contraceptives, we controlled for numerous demographic variables. However, we did not control for every issue that may have affected women’s choices. Also, our sample size was small for additional statistical controls. Of note, it was beyond the scope of this study to assess breastfeeding goals, mental health, or women’s preference for contraceptive features; studies to investigate those dimensions in the future may be fruitful. In addition, although we controlled for the type of diabetes and confounding by sociodemographic characteristics, there may be meaningful differences between women with T1DM and T2DM for which larger, separate samples would be needed to address.

control among adults with self-reported diagnosed diabetes— National Health and Nutrition Examination Survey, United States, 2007–2010. Morbidity and Mortality Weekly Report, 61(2), 32–37. Retrieved from https://www.cdc.gov/mmwr/ preview/mmwrhtml/su6102a6.htm American Diabetes Association. (2019). 14. Management of diabetes in pregnancy: Standards of medical care in diabetes—2019. Diabetes Care, 42(Suppl 1), S165–S172. Bardenheier, B. H., Imperatore, G., Devlin, H. M., Kim, S. Y., Cho, P., & Geiss, L.S.(2015).Trendsinpre-pregnancydiabetesamongdeliveriesin19 U.S. states, 2000–2010. American Journal of Preventive Medicine, 48(2), 154–161. https://doi.org/10.1016/j.amepre.2014.08.031 Barrett, G., Smith, S. C., & Wellings, K. (2004). Conceptualisation, development, and evaluation of a measure of unplanned pregnancy. Journal of Epidemiology and Community Health, 58(5), 426–433. https://doi.org/10.1136/JECH.2003.014787 Britton, L. E., Hussey, J. M., Crandell, J. L., Berry, D. C., Brooks, J. L., & Bryant, A. G. (2018). Racial/ethnic disparities in diabetes diagnosis and glycemic control among women of reproductive

Q11

These findings should not be generalized to women who were not included in our sample, including women who have severe complications, including fetal demise and significant malformations; those who do not speak English; and those who did not obtain perinatal care from an academic medical center. We collected data from cisgender women, and our findings may not address the needs of transgender or gender nonconforming individuals with diabetes.

age. Journal of Women’s Health, 27(10), 1271–1277. https://doi. org/10.1089/jwh.2017.6845 Britton, L. E., Hussey, J. M., Berry, D. C., Crandell, J. L., Brooks, J. L., & Bryant, A. G. (2019). Contraceptive use among women with prediabetes and diabetes in a US national sample. Journal of Midwifery & Women’s Health, 64(1), 36–45. https://doi.org/10. 1111/jmwh.12936 Centers for Disease Control and Prevention. (2016). National survey of family growth. Retrieved from https://www.cdc.gov/nchs/nsfg/ index.htm Charron-Prochownik, D., Fischl, A. F. R., Sereika, S. M., Malone, K., Schmitt, P., & Downs, J. (2015). Assessing reproductive health knowledge in female adolescents with diabetes. Plaid, 1(2), 24–

Q16

Conclusion

30. Retrieved from http://theplaidjournal.com/index.php/CoM/

Improving care in the postpartum period is critically important (Lowe, 2019), particularly for women managing chronic illnesses. Our findings highlight potential opportunities to improve maternity care for women with diabetes, which show promise for reducing future risks of adverse outcomes and supporting women to achieve their personal pregnancy goals.

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Q12

Chor, J., Rankin, K., Harwood, B., & Handler, A. (2011). Unintended

Acknowledgment

pregnancy and postpartum contraceptive use in women with

The authors thank Kim Boggess, Karen Dorman, Amber Ivins, Geraldine Barrett, Jenny Hall, Jon Hussey, and the READYGirls Team for Reproductive Health Attitudes and Behaviors.

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