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Published in: Demography 6/2020

30-11-2020

Material Hardship and Contraceptive Use During the Transition to Adulthood

Author: Elly Field

Published in: Demography | Issue 6/2020

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Abstract

Decades of research have attempted to understand the paradox of stubbornly high unintended pregnancy rates despite widespread use of contraception. Much of this research has focused on socioeconomic disparities in rates of unintended pregnancy, finding that economically disadvantaged women tend to use less effective contraceptive methods and use them less consistently. Building on this research, this study examines how material hardship is associated with less consistent contraceptive use among women who do not desire to become pregnant. Using the Relationship Dynamics and Social Life (RDSL) Study, a weekly longitudinal survey, I find lower levels of contraceptive use and less consistent use of contraception among women experiencing material hardship, relative to those without hardship experiences. I also investigate the extent to which this association is explained by access barriers and lower contraceptive efficacy among women experiencing hardship. Using structural equation modeling, I find that these mediators significantly explain the relationship between hardship and risky contraceptive behaviors, suggesting that hardship creates mental and resource constraints that impede successful implementation of contraception. However, net of these mediators, material hardship remains associated with riskier contraceptive behaviors among young women, calling for further research on how hardship exposes women to greater risk of unintended pregnancies.
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Appendix
Available only for authorised users
Footnotes
1
In supplementary analyses (Table A1, online appendix), I also show that women who do not desire pregnancy have very similar attitudes toward pregnancy and contraception, regardless of material hardship, indicating that riskier contraceptive behaviors among women experiencing hardship are not likely due to different attitudes.
 
2
Although this study design does control for cohort and age effects, survey administration during the beginning of the Great Recession may introduce period effects. Therefore, I provide a supplementary analysis of AddHealth.
 
3
The supplement was not introduced as an explicitly poverty-focused survey but rather as an additional survey on a range of topics, including school, jobs, and finances.
 
4
The RDSL has high response rates and low rates of attrition (Barber et al. 2016b; Watson and Wooden 2009), but comparing Poverty Supplement responders and nonresponders reveals that the nonresponders are generally more disadvantaged than responders. This is consistent with prior research and nonresponse bias on surveys. Models using chained multiple imputation on the hardship measures show similar results to models presented here, as well as a small conservative bias on some contraceptive behaviors.
 
5
Each week, women were asked whether they had sexual intercourse (defined as vaginal intercourse) and to rate how much they wanted to become pregnant in the next month or to avoid becoming pregnant on a scale of 0 to 5. The sample includes only those weeks in which women were both sexually active and reported having zero desire for pregnancy and the strongest desire to avoid pregnancy.
 
6
The RDSL captures any use of contraception, regardless of reason for using, following national surveys, like the NSFG. Contraception reduces unintended pregnancy risk even when women are using it for other reasons, such as acne treatment, severe PMS, or irregular menstrual cycles.
 
7
See Table A2 in the online appendix for the distributions of the dependent variables.
 
8
This measure includes only those weeks in which a coital-specific method was the woman’s most effective form of contraception. In addition, sensitivity analyses including only condom-use weeks showed substantively similar results, but the sample was considerably smaller.
 
9
Abortion rates are higher among African American women (Jones and Jerman 2017), which may also play a role in hardship because abortion may be a result of inconsistent contraception, and the expense of an abortion may cause hardship. Unfortunately, the RDSL is not well suited to analyses of abortion.
 
10
Only one respondent failed to complete all hardship questions, and she had no experiences of material hardship on the items that she completed. She was therefore coded as experiencing zero hardships.
 
11
Table A3 in the online appendix shows the distribution of hardship separately for women experiencing one hardship and women experiencing multiple hardships. This table shows that the distribution between these two groups is quite similar, with both groups most commonly experiencing pawning belongings, food insecurity, and telephone disconnection.
 
12
Supplemental analyses using different constructions of material hardship yielded substantively similar results and supported the decision to combine women experiencing multiple hardship into one group. Models including each hardship individually also did not find that any one hardship drives the relationship between hardship and contraceptive behaviors.
 
13
The study was conducted before the implementation of the Affordable Care Act and Medicaid expansion; I elaborate on implications of these policy changes in the discussion.
 
14
Results from the polychoric factor also supported including the measure on self-control with the measures of partner control. The Chronbach’s alpha for the scale with only the three partner measures was significantly lower than that for the four-item scale.
 
15
Alternative model specifications measure independence by whether a woman was living with her family and whether there was an interaction effect between independence and hardship. Both specifications provide substantively similar results.
 
16
Only one respondent was missing from the item on being responsible for oneself, and she was imputed as the mode (“not independent”). Nine respondents (2% of sample) were missing on family income at the Poverty Supplement and at baseline; these respondents were also imputed as the mode (“high family income”).
 
17
These measures were also tested as separate controls, but nearly none of the individual measures were significant. Therefore, I use the index measure to capture family background effects.
 
18
A sensitivity analysis using a dichotomous variable for White, compared to all other racial and ethnic groups, yielded nearly identical substantive results. A supplemental analysis including an interaction between race and material hardship indicated that the effect of hardship does not vary significantly by race.
 
19
See Ela and Budnick (2017) for additional comparisons of the RDSL sample to the nationally representative NSFG.
 
20
As a sensitivity analysis, I also included a control for ever expressing a desire for pregnancy during the survey and the proportion of weeks the woman was in a romantic relationship. These controls did not change the substantive results and were excluded in favor of the presented models, which provide a clean temporal ordering.
 
21
The AddHealth survey asks about lack of phone service, missed or underpayment of rent/mortgage, missed or underpayment of a utility bill, utility shutoff in the past 12 months, and current homelessness. The hardship measure captures whether a respondent said yes to any of these items.
 
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Metadata
Title
Material Hardship and Contraceptive Use During the Transition to Adulthood
Author
Elly Field
Publication date
30-11-2020
Publisher
Springer US
Published in
Demography / Issue 6/2020
Print ISSN: 0070-3370
Electronic ISSN: 1533-7790
DOI
https://doi.org/10.1007/s13524-020-00922-3

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