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Reasons for unprotected intercourse: analysis of the PRAMS survey
Contraception 75 (2007) 361 – 366
Original research article
Reasons for unprotected intercourse: analysis of the PRAMS survey Mary D. Nettlemana,4, Hwan Chungb, Jennifer Brewerc, Adejoke Ayoolad, Philip L. Reedb,e b
a Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, MI 48823, USA Department of Epidemiology, College of Human Medicine, Michigan State University, East Lansing, MI 48823, USA c Department of Anthropology, College of Social Science. East Lansing, MI 48823, USA d College of Nursing Michigan. East Lansing, MI 48823, USA e Biomedical Research and Informatics Center, Michigan State University, East Lansing, MI 48823, USA Received 21 November 2006; revised 1 January 2007; accepted 5 January 2007
Abstract Objectives: This study was conducted to identify reasons why women had unprotected intercourse that led to an unintended pregnancy. Methods: As part of the Pregnancy Risk Assessment Monitoring System (PRAMS) survey, women with a recent unintended viable pregnancy were asked after the birth why they had not used birth control. Results: Of 7856 respondents, 33% felt they could not get pregnant at the time of conception, 30% did not really mind if they got pregnant, 22% stated their partner did not want to use contraception, 16% cited side effects, 10% felt they or their partner were sterile, 10% cited access problems and 18% selected bother.Q Latent class analysis showed seven patterns of response, each identifying strongly with a single reason. Conclusions: Almost half of women with viable unintended pregnancies ending in a birth felt they could not/would not get pregnant at the time of conception. Most women identified with a single reason for having unprotected intercourse. D 2007 Elsevier Inc. All rights reserved. Keywords: Contraception; Pregnancy; Women’s health
1. Introduction Intercourse without contraception is common in the United States, even among women who wish to avoid pregnancy [1–5]. As a result of this bunprotected intercourse,Q unintended pregnancy is also common and represents an important public health issue [5–10]. In this era of effective contraception, it is not evident why women would have unprotected intercourse that puts them at risk for an unintended pregnancy. To develop effective interventions, it is clearly important to understand the reasons for unprotected intercourse. Moreover, it is possible that each woman has multiple reasons for having unprotected intercourse. An intervention that focused on eliminating a single reason might not reduce overall risk because a second equally important reason would remain unaddressed. To investigate these issues, we analyzed information from the Pregnancy Risk Assessment Monitoring System
4 Corresponding author: Tel.: +1 517 432 9124; fax: +1 517 432 9471. E-mail address: [email protected] (M.D. Nettleman). 0010-7824/$ – see front matter D 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.contraception.2007.01.011
(PRAMS). The population consisted of women who had engaged in unprotected intercourse resulting in an unintended viable pregnancy ending in a birth. The primary aims of this research were (a) to identify the reasons given by these women for having unprotected intercourse and (b) to evaluate if women typically had single or multiple reasons for having unprotected intercourse. 2. Materials and methods 2.1. Survey The PRAMS is a survey administered by the Centers for Disease Control and Prevention (CDC), in collaboration with state health departments [11]. The Michigan State University Institutional Review Board approved use of the PRAMS database, which does not contain any identifiers. For this analysis, we used the most current available data, which came from the PRAMS survey (Phase 4) administered in the years 2000–2002. Twenty-six states and New York City provided responses for the analysis. Each state drew a stratified systematic sample of new mothers every month from a frame of eligible birth certificates with the
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potential to oversample underrepresented groups such as low-birth-weight infants. The survey was mailed to the sample 2–4 months after delivery with telephone follow-up for those who did not respond to multiple mailings. Results were linked to birth certificate data. The PRAMS survey asked women to think back to just before they became pregnant and to describe how they felt about becoming pregnant. Women were classified as having intended pregnancies if they stated that they wanted to be pregnant at the time of conception or sooner. Women who stated that they wanted to become pregnant later or did not ever want to become pregnant were classified as having unintended pregnancies. Women with unintended pregnancies were then asked if they were bdoing anything to keep from getting pregnant.Q Examples of contraception were given. Women who were not bdoing anythingQ to prevent pregnancy were asked, bWhat were your or your husband’s or partner’s reasons for not doing anything to keep from getting pregnant?Q Thus, the question on reasons for unprotected intercourse was only answered by women who had self-described unintended pregnancies and who were not doing anything to prevent pregnancy. 2.2. Measures In PRAMS, the question about reasons for not using birth control was retrospectively measured by six items: (1) I did not mind if I got pregnant (Not mind); (2) I thought I could not get pregnant at that time (Timing); (3) I had side effects from the birth control method I was using (Side effect); (4) I had problems getting birth control when I needed it (Access); (5) I thought my husband or partner or I was sterile (Sterile) and (6) my partner did not want to use anything (Partner). The possible responses to these items were recorded to binary values of 1 for bNoQ and 2 for bYes.Q There was also an bother [specify]Q option (Other). Covariates that were included in the analysis were marital status (married or not married), age (b 18 or z 18 years), parity (parous or nulliparous prior to index pregnancy), race (white or nonwhite) and Medicaid status (whether or not Medicaid paid for the delivery). Dummy variables were created for all covariates. Including an intercept term, the full covariates vector for each individual had a length of six. Women were asked to give other reasons, if any, for not using birth control (Other). For the univariate and latent class (LC) analyses, we reduced this item to a binary indicator, recoded to 1 for giving any other reasons and 2 for not giving any other reason. This item was specified as a group variable, and the logistic coefficients were estimated separately for each group. The LC structure, however, was constrained to be equal across groups. The free-text responses to Other were also analyzed descriptively. Specifically, reasons were analyzed and sorted into categories independently by three authors (Nettleman et al. [12]). Disagreements were resolved by consensus. The
categories were based on previous focus group discussions with women who had unprotected intercourse [12]. Reasons that did not fit into one of the categories were reviewed to determine if a new category was needed. 2.3. Analysis Logistic regression analyses were performed to determine if any of the following covariates were associated with reason endorsement: age, marital status, race and parity. Socioeconomic status is not queried in PRAMS. However, as a surrogate, we included whether Medicaid paid for the delivery of the baby. Simultaneous adjustment for all five covariates was employed for each analysis. The analyses took into account the sampling design utilizing weights applied to each entity, reflecting the number of mothers the entity represented in the reference population [13]. The analysis weights were a composite of three elements of the sampling process, sample design, nonresponse and omissions in the sampling frame. To address the issue of whether women typically have multiple reasons for having unprotected intercourse, we employed the strategy of LC analysis using R 2.4.0 (R Developmental Core Team, www.R-project.org). The premise of LC modeling is that relationships among categorical variables arise because the population is composed of different classes. The population is assumed to consist of mutually exclusive and exhaustive groups, called LCs, and the distributions of the item responses vary across classes. LC analysis associates multiple manifest items through their class membership based on the assumption of local independence [13]. In LC models, rather than taking each response at face value, manifest items are treated as fallible indicators of unseen states that are subject to measurement error [14,15]. If an LC analysis fits well, it may provide a parsimonious and intuitively appealing summary of the cell frequencies in a high-dimensional contingency table and reveal features that are not apparent from an item-by-item analysis. LC models are designed to estimate the probability of study participants’ membership in hypothesized LCs and the item response probabilities given class membership.
3. Results There were 8600 women who reported unintended pregnancies and who were not using a method of pregnancy prevention. Of these, 7856 provided responses to the questions of interest (e.g., chose at least one foil or selecting Other), and this group comprised the study population. In this population, 3070 (39%) were married, 732 (9%) under the age of 18 and 3633 (46%) were previously nulliparous. In the study sample, 4383 (56%) of the women were white, 1956 (25%) were African American, 640 (8%) were Asian/ Pacific Islander/Hawaiian, 362 (5%) were Native Americans and 167 (2%) were Alaskan natives.
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Table 1 Cross tabulation and odds ratiosa for association of covariates with each reason for unprotected intercourse in the PRAMS population (n = 7856) Reason items
Endorsement Frequency (%)
Covariates odds ratios (95% CI) Age b 18 years
Nonmarried
Parous
White
Medicaid paid for delivery
Not mind Timing Side effect Access Sterile Partner Other
2331 2587 1241 758 767 1738 1429
0.49 1.19 0.56 1.15 0.88 1.74 1.48
0.50 1.08 1.10 1.67 1.31 1.27 1.01
0.78 0.78 1.40 1.30 0.58 1.02 1.39
1.05 0.83 0.81 1.31 1.10 0.81 1.04
0.71 1.40 1.09 1.82 1.12 1.19 0.92
a
(30) (33) (16) (10) (10) (22) (18)
(0.47–0.51) (1.15–1.22) (0.53–0.59) (1.10–1.20) (0.84–0.93) (1.69–1.80) (1.42–1.53)
(0.49–0.51) (1.06–1.10) (1.08–1.13) (1.62–1.72) (1.27–1.35) (1.24–1.30) (0.99–1.03)
(0.77–0.79) (0.77–0.80) (1.37–1.44) (1.26–1.33) (0.56–0.60) (1.00–1.04) (1.36–1.42)
(1.03–1.07) (0.82–0.85) (0.80–0.83) (1.28–1.35) (1.06–1.13) (0.80–0.83) (1.02–1.06)
(0.70–0.72) (1.37–1.42) (1.06–1.11) (1.77–1.86) (1.08–1.15) (1.17–1.21) (0.90–0.94)
Multicovariate logistic regression with simultaneous adjustment for all covariates.
With respect to the issue of multiple or complex reasons, most women (66%) endorsed only one reason or endorsed only Other (11%). Despite the fact that all women had an unintended pregnancy, 33% thought that they could not get pregnant at the time of intercourse, and 10% thought they or their partner were sterile (Table 1). Overall, 41% of women chose at least one of these two reasons. In addition, 30% stated that they did not mind if they got pregnant, even though all participants stated earlier in the survey that they did not want to get pregnant at the time or did not want to get pregnant ever. Results of the logistic regression analyses showed that although most of the associations were statistically significant, odds ratios were generally modest. Reasons did not cluster substantially or exclusively within a single demographic covariate. Examples of some of the stronger associations include: (1) women in the PRAMS population who did not mind if they got pregnant (Not mind) were more likely to be older, married, nulliparous and less likely to have Medicaid pay for the delivery (Table 1) [1]; (2) women who said they had unprotected intercourse because they experienced side effects from their birth control method (Side effect) were more likely to be younger, parous and nonwhite; (3) women who said, bI had problems getting birth control when I needed itQ (Access), were more likely to be unmarried, parous, white and had nearly twice the odds (OR =1.82) of having a Medicaid-paid delivery and (4) women with the reason bmy partner did not want to use anythingQ (Partner), were more likely to be younger unmarried and somewhat more likely to be nonwhite and to have Medicaid pay for the delivery. 3.1. Free text results There were 1429 women who selected Other (Table 2). Of these, 60% limited their response to the free text and did not choose any of the multiple choice responses in the PRAMS survey. The top three reasons — lack of thought, low perceived risk of pregnancy and did not know why/did not want to — represented 61% of the free-text responses. The most common free-text reason given was lack of thought or preparation. This category included women who stated that they bjust were not thinking,Q were bcarelessQ or who ran out of their method but still had sex. There were
131 women who provided a vague response, including 44 who said they bjust did notQ use contraception, 33 who said they bdid not wantQ to use birth control and 33 who stated they had bno reasonQ or bdid not knowQ why they did not use contraception. Being at low risk for pregnancy was given as a free-text reason for having unprotected intercourse by 258 women. Of these, 46 women had had unprotected intercourse for some time (months to years) without getting pregnant or had infertility problems in the past and therefore thought they were unlikely to conceive. There were 57 women who thought they were at low risk because they were still breastfeeding another child, 17 who thought they were at low risk due to a recent miscarriage and 11 who thought they were at low risk because they had just had a baby. Thirty-two women stated that a doctor or health care worker had told them they were unable to get pregnant. Fifteen cited specific medical conditions that they felt put them at low risk of
Table 2 Reasons for unprotected intercourse: free-text responses to botherQ
Lack of thought or preparation Thought she was at low risk for pregnancy Did not know why or just did not want to Miscellaneous Relied on alternative method such as withdrawal Worried about side effects Ambivalent attitude towards pregnancy Too costly Pre-existing condition limits choice of contraception Incomplete answer Against religious beliefs Partner did not want her to use birth control Rape or forced intercourse Believe products are ineffective Access problems Shy or embarrassed Technical difficulties Partner does not like condoms Feared using contraception would have a negative impact on relationship with partner
Frequency
Percent (n = 1429)
486 258 131 107 92
34 18 9 7.5 6
68 52 51 44
5 4 4 3
43 26 18 17 14 8 5 5 2 2
3 2 1 1 1 1 0.3 0.3 0.1 0.1
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Table 3 Fit statistics, degrees of freedom for a series of LC models without covariates Number of classes
AIC
BIC
G 2 statistic
Degrees of freedom
Normed-fit index
2 3 4 5 6 7 8
1549.72 1070.82 858.62 654.84 379.70 167.37 161.77
1640.32 1210.20 1046.78 891.79 665.43 501.88 545.06
1523.72 1030.82 804.62 586.84 297.70 71.37 51.77
50 43 36 29 22 15 8
0.32 0.22 0.27 0.49 0.76 0.27
AIC and BIC are goodness-of-fit measures which adjust G 2 statistic by penalizing for model complexity. The G 2 statistic compares the predicted response pattern frequencies with the observed frequencies. The normed fit index is defined as the proportion of the (L+1) class models drop in G 2 compared with the G 2 value of the LC model.
compared by using penalized likelihood criteria such as AIC [16] and BIC [17]. The penalized likelihood criteria (AIC and BIC) and the relative decrements in G 2, called the normed fit index, are reported in Table 3 [18,19]. Lower AIC or BIC values are associated with better models. The fit index is a popular descriptive statistic in structural equation modeling [20]. Table 3 shows large drops in G 2 as the number of classes increases from 5 to 6 (49%) and from 6 to 7 (76%), but much smaller drop from 7 to 8 (27%). Therefore, a sevenclass model was selected. Estimates for all item response probabilities from sevenclass model are shown in Table 4. These were computed by maximum likelihood using the expectation–maximization algorithm. Examining the estimates from Table 4, we see that six of the classes were identified strongly with a single reason. For example, class II represented a subpopulation that identified strongly with having a partner who did not want to use contraception (Partner). Class III identified strongly with the reason bI thought I or my partner were sterileQ (Sterile). The exception was class I, representing a subpopulation that identified with no reason, but did select Other. Conversely, of those who selected Other, 60% were in Class I. The probability of belonging to each class is also shown in Table 4. Class VII was the largest class with 22% of the population and represented women who strongly identified with Not mind. Women who felt that they could not get pregnant included those who felt they could not get pregnant at the time of intercourse (Timing) and those who thought they or their partner were sterile
pregnancy, including endometriosis, tilted uterus, polycystic ovary syndrome, menses irregularities, diabetes or a history of cancer. Thirteen women stated that they thought their partner was sterile. Two women stated they were too young to get pregnant, and four women stated they were too old. Among the remainder, several women just stated that they did not think they could get pregnant or that they did not think it would happen so fast. Of the 263 women, 135 (51%) did not select any of the multiple-choice reasons listed in the survey. There were 52 women who were ambivalent about wanting pregnancy and provided a free-text explanation. Of these, 15 stated that they left the timing of a pregnancy in the hands of God, nature or fate. Five women stated that they were in love or in a stable relationship. The remainder simply stated that it did not matter if they became pregnant. Of the 1429 responses, 107 were classified as bmiscellaneous.Q In general, these responses did not clearly address the reason for unprotected intercourse and included women who stated that they had used birth control in the past, that they were waiting to get on birth control or that their partner deceived them about his fertility/condom use. They also included women who selected Other but who left the free-text field blank. 3.2. Latent class analysis The first and most crucial step in an LC analysis is to choose an appropriate class structure. In the absence of strong prior beliefs, the number of classes is usually chosen to strike a balance between parsimony, fit and interpretability. Models with different number of classes are typically Table 4 Reasons for unprotected intercourse: results of LC analysis Class
I
II
III
IV
V
VI
VII
Membership (% of population)
11
19
9.8
6.5
12.2
19.6
22.0
0.000 0.000 0.000 0.000 0.000 0.000
0.165 0.251 0.109 0.087 0.000 1.000
0.179 0.387 0.129 0.072 1.000 0.190
0.049 0.139 0.000 1.000 0.000 0.000
0.163 0.177 1.000 0.052 0.000 0.061
0.034 1.000 0.000 0.000 0.000 0.000
1.000 0.085 0.014 0.010 0.000 0.029
Item-response probabilitiesa Not mind Timing Side effect Access Sterile Partner a
Probability of answering byesQ to foil by class.
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(Sterile) and were most strongly identified with Classes III and VI. Combined, these two classes represented 29% of the population. 4. Discussion This study provides important insight into reasons for unprotected intercourse leading to an unintended pregnancy ending in a birth. Forty-two percent of women felt that they could not become pregnant at the time of intercourse and/or that they or their partner were sterile. Since all of these women actually became pregnant, that belief was obviously erroneous. Of women who gave a free-text reason related to low pregnancy risk, the principal explanation was that they were breast-feeding or had just had a baby or a miscarriage. Although pregnancy rates are as low as 1% per year in women who have lactational amenorrhea and are breast-feeding full-time [21–23], rates are higher in other postpartum women. Improved education may help women make an informed choice regarding birth control during lactation. Of concern, some women stated that they had been told by a health care worker that they could not become pregnant. Other women felt they were unable to conceive because of medical conditions. This belief argues for an educational effort directed at healthcare personnel to ensure that women receive clear messages about their risk of pregnancy. Some women felt they were at low risk of pregnancy because that they had trouble becoming pregnant in the past or because they had previous episodes of unprotected intercourse without getting pregnant. The risk of pregnancy depends on several factors, including the timing of intercourse and ovulation [24,25]. Women of childbearing age should assume that they have a finite risk of pregnancy with every episode of unprotected intercourse. Ambivalence about pregnancy was common. Unintendedness in this study was defined traditionally as a mistimed or unwanted pregnancy. Although all women had an unintended pregnancy, 30% stated that they did not mind if they became pregnant. This seeming paradox has been described by others [26–29]. Although useful for identifying pregnancies at risk for adverse outcomes [5–10], the concept of intendedness does not appear to be widely recognized by pregnant women. Latent class analysis revealed little evidence supporting the existence of subgroups characterized by complex patterns of multiple reasons. Six of the seven classes were primarily characterized by a dominant single reason. This finding is encouraging because it implies that addressing a single reason might directly affect behavior. However, it is important to note that the PRAMS questions asked women about the time just before they became pregnant. Thus, it is not possible to state whether women might endorse different reasons over longer time frames. In addition, only a limited number of choices were provided in the question.
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In general, the reasons listed by the PRAMS questionnaire were widely recognized, with 89% of women choosing at least one of the multiple-choice responses. However, one in five women felt compelled to specify a free-text reason. Almost half of these Other reasons could be picked up if the multiple choice question included two additional responses: lack of thought/preparation and do not know/just did not want to. These reasons argue for a lack of motivation in women who do not actively manage their fertility and provide an opportunity for motivational interventions. This study is subject to several limitations. The sample is not nationally representative, which limits the ability to extrapolate the results to the general population or to special populations. For example, only 9% of the population was under 18 years of age. In addition, information was obtained after delivery and thus was subject to recall bias. Women who answered the question about reasons for unprotected intercourse were limited to those who had unintended pregnancies and were not doing anything to prevent pregnancy. Women who were using a form of birth control, albeit imperfectly, skipped over the reasons question. In summary, there are several reasons why women had unprotected intercourse that led to an unintended pregnancy. The results show a need to raise awareness of pregnancy risk and to explore the concept of intendedness. Acknowledgments We gratefully acknowledge the following for providing the PRAMS database: the PRAMS Working Group: Alabama, Albert Woolbright, Ph.D.; Alaska, Kathy Perham, Hester, M.S., M.P.H.; Arkansas, Gina Redford, M.A.P.; Colorado, Alyson Shupe, Ph.D.; Florida, Helen Marshall; Georgia, Carol Hoban, M.S., M.P.H.; Hawaii, Limin Song, M.P.H., C.H.E.S.; Illinois, Theresa Sandidge, M.A.; Louisiana, Joan Wightkin; Maine, Kim Haggan; Maryland, Diana Cheng, M.D.; Michigan, Yasmina Bouraoui, M.P.H.; Minnesota, Jan Jernell; Mississippi, Linda Pendleton, L.M.S.W.; Montana, JoAnn Dotson; Nebraska, Jennifer Severe-Oforah; New Jersey, Lakota Kruse, M.D.; New Mexico, Ssu Weng, M.D., M.P.H.; New York State, Anne Radigan-Garcia; New York City, Candace Mulready, M.P.H.; North Carolina, Paul Buescher, Ph.D.; North Dakota, Sandra Anseth, R.N.; Ohio, Amy Davis; Oklahoma, Dick Lorenz; Oregon, Ken Rosenberg, M.D., M.P.H.; Rhode Island, Sam Viner-Brown; South Carolina, Jim Ferguson, Dr.P.H.; Texas, Tanya J. Guthrie, Ph.D.; Utah, Laurie Baksh; Vermont, Peggy Brozicevic; Washington, Linda Lohdefinck; West Virginia, Melissa Baker, M.A.; CDC PRAMS Team, Applied Sciences Branch, Division of Reproductive Health. We also acknowledge the CDC, The US Department of Health and Human Services, Health Resource Services Administration, Maternal and Child Health Bureau and the Oklahoma State Department of Health, Maternal and Child Health Service PRAMS Project.
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Original research article
Reasons for unprotected intercourse: analysis of the PRAMS survey Mary D. Nettlemana,4, Hwan Chungb, Jennifer Brewerc, Adejoke Ayoolad, Philip L. Reedb,e b
a Department of Medicine, College of Human Medicine, Michigan State University, East Lansing, MI 48823, USA Department of Epidemiology, College of Human Medicine, Michigan State University, East Lansing, MI 48823, USA c Department of Anthropology, College of Social Science. East Lansing, MI 48823, USA d College of Nursing Michigan. East Lansing, MI 48823, USA e Biomedical Research and Informatics Center, Michigan State University, East Lansing, MI 48823, USA Received 21 November 2006; revised 1 January 2007; accepted 5 January 2007
Abstract Objectives: This study was conducted to identify reasons why women had unprotected intercourse that led to an unintended pregnancy. Methods: As part of the Pregnancy Risk Assessment Monitoring System (PRAMS) survey, women with a recent unintended viable pregnancy were asked after the birth why they had not used birth control. Results: Of 7856 respondents, 33% felt they could not get pregnant at the time of conception, 30% did not really mind if they got pregnant, 22% stated their partner did not want to use contraception, 16% cited side effects, 10% felt they or their partner were sterile, 10% cited access problems and 18% selected bother.Q Latent class analysis showed seven patterns of response, each identifying strongly with a single reason. Conclusions: Almost half of women with viable unintended pregnancies ending in a birth felt they could not/would not get pregnant at the time of conception. Most women identified with a single reason for having unprotected intercourse. D 2007 Elsevier Inc. All rights reserved. Keywords: Contraception; Pregnancy; Women’s health
1. Introduction Intercourse without contraception is common in the United States, even among women who wish to avoid pregnancy [1–5]. As a result of this bunprotected intercourse,Q unintended pregnancy is also common and represents an important public health issue [5–10]. In this era of effective contraception, it is not evident why women would have unprotected intercourse that puts them at risk for an unintended pregnancy. To develop effective interventions, it is clearly important to understand the reasons for unprotected intercourse. Moreover, it is possible that each woman has multiple reasons for having unprotected intercourse. An intervention that focused on eliminating a single reason might not reduce overall risk because a second equally important reason would remain unaddressed. To investigate these issues, we analyzed information from the Pregnancy Risk Assessment Monitoring System
4 Corresponding author: Tel.: +1 517 432 9124; fax: +1 517 432 9471. E-mail address: [email protected] (M.D. Nettleman). 0010-7824/$ – see front matter D 2007 Elsevier Inc. All rights reserved. doi:10.1016/j.contraception.2007.01.011
(PRAMS). The population consisted of women who had engaged in unprotected intercourse resulting in an unintended viable pregnancy ending in a birth. The primary aims of this research were (a) to identify the reasons given by these women for having unprotected intercourse and (b) to evaluate if women typically had single or multiple reasons for having unprotected intercourse. 2. Materials and methods 2.1. Survey The PRAMS is a survey administered by the Centers for Disease Control and Prevention (CDC), in collaboration with state health departments [11]. The Michigan State University Institutional Review Board approved use of the PRAMS database, which does not contain any identifiers. For this analysis, we used the most current available data, which came from the PRAMS survey (Phase 4) administered in the years 2000–2002. Twenty-six states and New York City provided responses for the analysis. Each state drew a stratified systematic sample of new mothers every month from a frame of eligible birth certificates with the
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potential to oversample underrepresented groups such as low-birth-weight infants. The survey was mailed to the sample 2–4 months after delivery with telephone follow-up for those who did not respond to multiple mailings. Results were linked to birth certificate data. The PRAMS survey asked women to think back to just before they became pregnant and to describe how they felt about becoming pregnant. Women were classified as having intended pregnancies if they stated that they wanted to be pregnant at the time of conception or sooner. Women who stated that they wanted to become pregnant later or did not ever want to become pregnant were classified as having unintended pregnancies. Women with unintended pregnancies were then asked if they were bdoing anything to keep from getting pregnant.Q Examples of contraception were given. Women who were not bdoing anythingQ to prevent pregnancy were asked, bWhat were your or your husband’s or partner’s reasons for not doing anything to keep from getting pregnant?Q Thus, the question on reasons for unprotected intercourse was only answered by women who had self-described unintended pregnancies and who were not doing anything to prevent pregnancy. 2.2. Measures In PRAMS, the question about reasons for not using birth control was retrospectively measured by six items: (1) I did not mind if I got pregnant (Not mind); (2) I thought I could not get pregnant at that time (Timing); (3) I had side effects from the birth control method I was using (Side effect); (4) I had problems getting birth control when I needed it (Access); (5) I thought my husband or partner or I was sterile (Sterile) and (6) my partner did not want to use anything (Partner). The possible responses to these items were recorded to binary values of 1 for bNoQ and 2 for bYes.Q There was also an bother [specify]Q option (Other). Covariates that were included in the analysis were marital status (married or not married), age (b 18 or z 18 years), parity (parous or nulliparous prior to index pregnancy), race (white or nonwhite) and Medicaid status (whether or not Medicaid paid for the delivery). Dummy variables were created for all covariates. Including an intercept term, the full covariates vector for each individual had a length of six. Women were asked to give other reasons, if any, for not using birth control (Other). For the univariate and latent class (LC) analyses, we reduced this item to a binary indicator, recoded to 1 for giving any other reasons and 2 for not giving any other reason. This item was specified as a group variable, and the logistic coefficients were estimated separately for each group. The LC structure, however, was constrained to be equal across groups. The free-text responses to Other were also analyzed descriptively. Specifically, reasons were analyzed and sorted into categories independently by three authors (Nettleman et al. [12]). Disagreements were resolved by consensus. The
categories were based on previous focus group discussions with women who had unprotected intercourse [12]. Reasons that did not fit into one of the categories were reviewed to determine if a new category was needed. 2.3. Analysis Logistic regression analyses were performed to determine if any of the following covariates were associated with reason endorsement: age, marital status, race and parity. Socioeconomic status is not queried in PRAMS. However, as a surrogate, we included whether Medicaid paid for the delivery of the baby. Simultaneous adjustment for all five covariates was employed for each analysis. The analyses took into account the sampling design utilizing weights applied to each entity, reflecting the number of mothers the entity represented in the reference population [13]. The analysis weights were a composite of three elements of the sampling process, sample design, nonresponse and omissions in the sampling frame. To address the issue of whether women typically have multiple reasons for having unprotected intercourse, we employed the strategy of LC analysis using R 2.4.0 (R Developmental Core Team, www.R-project.org). The premise of LC modeling is that relationships among categorical variables arise because the population is composed of different classes. The population is assumed to consist of mutually exclusive and exhaustive groups, called LCs, and the distributions of the item responses vary across classes. LC analysis associates multiple manifest items through their class membership based on the assumption of local independence [13]. In LC models, rather than taking each response at face value, manifest items are treated as fallible indicators of unseen states that are subject to measurement error [14,15]. If an LC analysis fits well, it may provide a parsimonious and intuitively appealing summary of the cell frequencies in a high-dimensional contingency table and reveal features that are not apparent from an item-by-item analysis. LC models are designed to estimate the probability of study participants’ membership in hypothesized LCs and the item response probabilities given class membership.
3. Results There were 8600 women who reported unintended pregnancies and who were not using a method of pregnancy prevention. Of these, 7856 provided responses to the questions of interest (e.g., chose at least one foil or selecting Other), and this group comprised the study population. In this population, 3070 (39%) were married, 732 (9%) under the age of 18 and 3633 (46%) were previously nulliparous. In the study sample, 4383 (56%) of the women were white, 1956 (25%) were African American, 640 (8%) were Asian/ Pacific Islander/Hawaiian, 362 (5%) were Native Americans and 167 (2%) were Alaskan natives.
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Table 1 Cross tabulation and odds ratiosa for association of covariates with each reason for unprotected intercourse in the PRAMS population (n = 7856) Reason items
Endorsement Frequency (%)
Covariates odds ratios (95% CI) Age b 18 years
Nonmarried
Parous
White
Medicaid paid for delivery
Not mind Timing Side effect Access Sterile Partner Other
2331 2587 1241 758 767 1738 1429
0.49 1.19 0.56 1.15 0.88 1.74 1.48
0.50 1.08 1.10 1.67 1.31 1.27 1.01
0.78 0.78 1.40 1.30 0.58 1.02 1.39
1.05 0.83 0.81 1.31 1.10 0.81 1.04
0.71 1.40 1.09 1.82 1.12 1.19 0.92
a
(30) (33) (16) (10) (10) (22) (18)
(0.47–0.51) (1.15–1.22) (0.53–0.59) (1.10–1.20) (0.84–0.93) (1.69–1.80) (1.42–1.53)
(0.49–0.51) (1.06–1.10) (1.08–1.13) (1.62–1.72) (1.27–1.35) (1.24–1.30) (0.99–1.03)
(0.77–0.79) (0.77–0.80) (1.37–1.44) (1.26–1.33) (0.56–0.60) (1.00–1.04) (1.36–1.42)
(1.03–1.07) (0.82–0.85) (0.80–0.83) (1.28–1.35) (1.06–1.13) (0.80–0.83) (1.02–1.06)
(0.70–0.72) (1.37–1.42) (1.06–1.11) (1.77–1.86) (1.08–1.15) (1.17–1.21) (0.90–0.94)
Multicovariate logistic regression with simultaneous adjustment for all covariates.
With respect to the issue of multiple or complex reasons, most women (66%) endorsed only one reason or endorsed only Other (11%). Despite the fact that all women had an unintended pregnancy, 33% thought that they could not get pregnant at the time of intercourse, and 10% thought they or their partner were sterile (Table 1). Overall, 41% of women chose at least one of these two reasons. In addition, 30% stated that they did not mind if they got pregnant, even though all participants stated earlier in the survey that they did not want to get pregnant at the time or did not want to get pregnant ever. Results of the logistic regression analyses showed that although most of the associations were statistically significant, odds ratios were generally modest. Reasons did not cluster substantially or exclusively within a single demographic covariate. Examples of some of the stronger associations include: (1) women in the PRAMS population who did not mind if they got pregnant (Not mind) were more likely to be older, married, nulliparous and less likely to have Medicaid pay for the delivery (Table 1) [1]; (2) women who said they had unprotected intercourse because they experienced side effects from their birth control method (Side effect) were more likely to be younger, parous and nonwhite; (3) women who said, bI had problems getting birth control when I needed itQ (Access), were more likely to be unmarried, parous, white and had nearly twice the odds (OR =1.82) of having a Medicaid-paid delivery and (4) women with the reason bmy partner did not want to use anythingQ (Partner), were more likely to be younger unmarried and somewhat more likely to be nonwhite and to have Medicaid pay for the delivery. 3.1. Free text results There were 1429 women who selected Other (Table 2). Of these, 60% limited their response to the free text and did not choose any of the multiple choice responses in the PRAMS survey. The top three reasons — lack of thought, low perceived risk of pregnancy and did not know why/did not want to — represented 61% of the free-text responses. The most common free-text reason given was lack of thought or preparation. This category included women who stated that they bjust were not thinking,Q were bcarelessQ or who ran out of their method but still had sex. There were
131 women who provided a vague response, including 44 who said they bjust did notQ use contraception, 33 who said they bdid not wantQ to use birth control and 33 who stated they had bno reasonQ or bdid not knowQ why they did not use contraception. Being at low risk for pregnancy was given as a free-text reason for having unprotected intercourse by 258 women. Of these, 46 women had had unprotected intercourse for some time (months to years) without getting pregnant or had infertility problems in the past and therefore thought they were unlikely to conceive. There were 57 women who thought they were at low risk because they were still breastfeeding another child, 17 who thought they were at low risk due to a recent miscarriage and 11 who thought they were at low risk because they had just had a baby. Thirty-two women stated that a doctor or health care worker had told them they were unable to get pregnant. Fifteen cited specific medical conditions that they felt put them at low risk of
Table 2 Reasons for unprotected intercourse: free-text responses to botherQ
Lack of thought or preparation Thought she was at low risk for pregnancy Did not know why or just did not want to Miscellaneous Relied on alternative method such as withdrawal Worried about side effects Ambivalent attitude towards pregnancy Too costly Pre-existing condition limits choice of contraception Incomplete answer Against religious beliefs Partner did not want her to use birth control Rape or forced intercourse Believe products are ineffective Access problems Shy or embarrassed Technical difficulties Partner does not like condoms Feared using contraception would have a negative impact on relationship with partner
Frequency
Percent (n = 1429)
486 258 131 107 92
34 18 9 7.5 6
68 52 51 44
5 4 4 3
43 26 18 17 14 8 5 5 2 2
3 2 1 1 1 1 0.3 0.3 0.1 0.1
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Table 3 Fit statistics, degrees of freedom for a series of LC models without covariates Number of classes
AIC
BIC
G 2 statistic
Degrees of freedom
Normed-fit index
2 3 4 5 6 7 8
1549.72 1070.82 858.62 654.84 379.70 167.37 161.77
1640.32 1210.20 1046.78 891.79 665.43 501.88 545.06
1523.72 1030.82 804.62 586.84 297.70 71.37 51.77
50 43 36 29 22 15 8
0.32 0.22 0.27 0.49 0.76 0.27
AIC and BIC are goodness-of-fit measures which adjust G 2 statistic by penalizing for model complexity. The G 2 statistic compares the predicted response pattern frequencies with the observed frequencies. The normed fit index is defined as the proportion of the (L+1) class models drop in G 2 compared with the G 2 value of the LC model.
compared by using penalized likelihood criteria such as AIC [16] and BIC [17]. The penalized likelihood criteria (AIC and BIC) and the relative decrements in G 2, called the normed fit index, are reported in Table 3 [18,19]. Lower AIC or BIC values are associated with better models. The fit index is a popular descriptive statistic in structural equation modeling [20]. Table 3 shows large drops in G 2 as the number of classes increases from 5 to 6 (49%) and from 6 to 7 (76%), but much smaller drop from 7 to 8 (27%). Therefore, a sevenclass model was selected. Estimates for all item response probabilities from sevenclass model are shown in Table 4. These were computed by maximum likelihood using the expectation–maximization algorithm. Examining the estimates from Table 4, we see that six of the classes were identified strongly with a single reason. For example, class II represented a subpopulation that identified strongly with having a partner who did not want to use contraception (Partner). Class III identified strongly with the reason bI thought I or my partner were sterileQ (Sterile). The exception was class I, representing a subpopulation that identified with no reason, but did select Other. Conversely, of those who selected Other, 60% were in Class I. The probability of belonging to each class is also shown in Table 4. Class VII was the largest class with 22% of the population and represented women who strongly identified with Not mind. Women who felt that they could not get pregnant included those who felt they could not get pregnant at the time of intercourse (Timing) and those who thought they or their partner were sterile
pregnancy, including endometriosis, tilted uterus, polycystic ovary syndrome, menses irregularities, diabetes or a history of cancer. Thirteen women stated that they thought their partner was sterile. Two women stated they were too young to get pregnant, and four women stated they were too old. Among the remainder, several women just stated that they did not think they could get pregnant or that they did not think it would happen so fast. Of the 263 women, 135 (51%) did not select any of the multiple-choice reasons listed in the survey. There were 52 women who were ambivalent about wanting pregnancy and provided a free-text explanation. Of these, 15 stated that they left the timing of a pregnancy in the hands of God, nature or fate. Five women stated that they were in love or in a stable relationship. The remainder simply stated that it did not matter if they became pregnant. Of the 1429 responses, 107 were classified as bmiscellaneous.Q In general, these responses did not clearly address the reason for unprotected intercourse and included women who stated that they had used birth control in the past, that they were waiting to get on birth control or that their partner deceived them about his fertility/condom use. They also included women who selected Other but who left the free-text field blank. 3.2. Latent class analysis The first and most crucial step in an LC analysis is to choose an appropriate class structure. In the absence of strong prior beliefs, the number of classes is usually chosen to strike a balance between parsimony, fit and interpretability. Models with different number of classes are typically Table 4 Reasons for unprotected intercourse: results of LC analysis Class
I
II
III
IV
V
VI
VII
Membership (% of population)
11
19
9.8
6.5
12.2
19.6
22.0
0.000 0.000 0.000 0.000 0.000 0.000
0.165 0.251 0.109 0.087 0.000 1.000
0.179 0.387 0.129 0.072 1.000 0.190
0.049 0.139 0.000 1.000 0.000 0.000
0.163 0.177 1.000 0.052 0.000 0.061
0.034 1.000 0.000 0.000 0.000 0.000
1.000 0.085 0.014 0.010 0.000 0.029
Item-response probabilitiesa Not mind Timing Side effect Access Sterile Partner a
Probability of answering byesQ to foil by class.
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(Sterile) and were most strongly identified with Classes III and VI. Combined, these two classes represented 29% of the population. 4. Discussion This study provides important insight into reasons for unprotected intercourse leading to an unintended pregnancy ending in a birth. Forty-two percent of women felt that they could not become pregnant at the time of intercourse and/or that they or their partner were sterile. Since all of these women actually became pregnant, that belief was obviously erroneous. Of women who gave a free-text reason related to low pregnancy risk, the principal explanation was that they were breast-feeding or had just had a baby or a miscarriage. Although pregnancy rates are as low as 1% per year in women who have lactational amenorrhea and are breast-feeding full-time [21–23], rates are higher in other postpartum women. Improved education may help women make an informed choice regarding birth control during lactation. Of concern, some women stated that they had been told by a health care worker that they could not become pregnant. Other women felt they were unable to conceive because of medical conditions. This belief argues for an educational effort directed at healthcare personnel to ensure that women receive clear messages about their risk of pregnancy. Some women felt they were at low risk of pregnancy because that they had trouble becoming pregnant in the past or because they had previous episodes of unprotected intercourse without getting pregnant. The risk of pregnancy depends on several factors, including the timing of intercourse and ovulation [24,25]. Women of childbearing age should assume that they have a finite risk of pregnancy with every episode of unprotected intercourse. Ambivalence about pregnancy was common. Unintendedness in this study was defined traditionally as a mistimed or unwanted pregnancy. Although all women had an unintended pregnancy, 30% stated that they did not mind if they became pregnant. This seeming paradox has been described by others [26–29]. Although useful for identifying pregnancies at risk for adverse outcomes [5–10], the concept of intendedness does not appear to be widely recognized by pregnant women. Latent class analysis revealed little evidence supporting the existence of subgroups characterized by complex patterns of multiple reasons. Six of the seven classes were primarily characterized by a dominant single reason. This finding is encouraging because it implies that addressing a single reason might directly affect behavior. However, it is important to note that the PRAMS questions asked women about the time just before they became pregnant. Thus, it is not possible to state whether women might endorse different reasons over longer time frames. In addition, only a limited number of choices were provided in the question.
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In general, the reasons listed by the PRAMS questionnaire were widely recognized, with 89% of women choosing at least one of the multiple-choice responses. However, one in five women felt compelled to specify a free-text reason. Almost half of these Other reasons could be picked up if the multiple choice question included two additional responses: lack of thought/preparation and do not know/just did not want to. These reasons argue for a lack of motivation in women who do not actively manage their fertility and provide an opportunity for motivational interventions. This study is subject to several limitations. The sample is not nationally representative, which limits the ability to extrapolate the results to the general population or to special populations. For example, only 9% of the population was under 18 years of age. In addition, information was obtained after delivery and thus was subject to recall bias. Women who answered the question about reasons for unprotected intercourse were limited to those who had unintended pregnancies and were not doing anything to prevent pregnancy. Women who were using a form of birth control, albeit imperfectly, skipped over the reasons question. In summary, there are several reasons why women had unprotected intercourse that led to an unintended pregnancy. The results show a need to raise awareness of pregnancy risk and to explore the concept of intendedness. Acknowledgments We gratefully acknowledge the following for providing the PRAMS database: the PRAMS Working Group: Alabama, Albert Woolbright, Ph.D.; Alaska, Kathy Perham, Hester, M.S., M.P.H.; Arkansas, Gina Redford, M.A.P.; Colorado, Alyson Shupe, Ph.D.; Florida, Helen Marshall; Georgia, Carol Hoban, M.S., M.P.H.; Hawaii, Limin Song, M.P.H., C.H.E.S.; Illinois, Theresa Sandidge, M.A.; Louisiana, Joan Wightkin; Maine, Kim Haggan; Maryland, Diana Cheng, M.D.; Michigan, Yasmina Bouraoui, M.P.H.; Minnesota, Jan Jernell; Mississippi, Linda Pendleton, L.M.S.W.; Montana, JoAnn Dotson; Nebraska, Jennifer Severe-Oforah; New Jersey, Lakota Kruse, M.D.; New Mexico, Ssu Weng, M.D., M.P.H.; New York State, Anne Radigan-Garcia; New York City, Candace Mulready, M.P.H.; North Carolina, Paul Buescher, Ph.D.; North Dakota, Sandra Anseth, R.N.; Ohio, Amy Davis; Oklahoma, Dick Lorenz; Oregon, Ken Rosenberg, M.D., M.P.H.; Rhode Island, Sam Viner-Brown; South Carolina, Jim Ferguson, Dr.P.H.; Texas, Tanya J. Guthrie, Ph.D.; Utah, Laurie Baksh; Vermont, Peggy Brozicevic; Washington, Linda Lohdefinck; West Virginia, Melissa Baker, M.A.; CDC PRAMS Team, Applied Sciences Branch, Division of Reproductive Health. We also acknowledge the CDC, The US Department of Health and Human Services, Health Resource Services Administration, Maternal and Child Health Bureau and the Oklahoma State Department of Health, Maternal and Child Health Service PRAMS Project.
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