Teen Motherhood and Long-Term Health Consequences

Teen Motherhood and Long-Term Health Consequences

Payal H. Patel • Bisakha Sen

Published online: 8 June 2011

� Springer Science+Business Media, LLC 2011

Abstract The objective of this article is to examine the

association of teen motherhood and long-term physical and

mental health outcomes. The physical and mental health

components (PCS and MCS) of the SF-12 Healthy Survey

in the NLSY79 health module were used to assess long-

term health outcomes of women who experienced teenage

motherhood. Various familial, demographic, and environ-

mental characteristics were indentified and controlled for

that may have predicted teen motherhood and long-term

health outcomes. The two comparison groups for teen

mothers were women who experienced teen-pregnancy

only and women who were engaged in unprotected sexual

activity as a teenage but did not experience pregnancy.

Multivariate ordinary least squares regression was used for

analysis. The average PCS and MCS for teen mothers was

49.91 and 50.89, respectively. Teen mothers exhibited

poorer physical health later in life compared to all women

as well as the comparison groups. When controlling for

age, teen mothers had significantly lower PCS and MCS

scores compared to all other women. Furthermore, when

controlling for familial, demographic, and environmental

characteristics, teen mothers exhibited significantly lower

PCS and MCS scores. When comparing teen mothers to the

two comparison groups, PCS was not statistically different

although MCS was significantly lower in the teen-preg-

nancy group. Teen motherhood does lead to poorer phys-

ical health outcomes later in life. On the other hand, poorer

mental health outcomes in later life may be attributed to the

unmeasured factors leading to a teen pregnancy and not

teen motherhood itself. Additional research needs to be

conducted on the long-term consequences of teen


Keywords Teen motherhood � Physical health � Mental health � Health outcomes


The US has continued to experience higher rates of teenage

pregnancy and motherhood than most developed nations

[1]. Each year, approximately 750,000 women aged 15–19

experience a pregnancy [2] and the majority of these

pregnancies result in live births. After falling to a low of

40.5 births per 1,000 women in 2005, the average birth

rates for 15–19 year olds increased in 2006 to 41.9 births

per 1,000 women. Approximately 10% of all US births in

2006 were to teenagers [3].

The total annual government expenditures on public aid

to teen-mothers in 2006 were $11.3 billion [3]. But apart

from the costs imposed upon taxpayers, teen-mothers

themselves exhibit adverse outcomes subsequently in life,

including poor educational and economic outcomes. In this

study, we extend that literature by exploring the relation-

ship between teen-motherhood and mid-life health out-

comes for women. Little research has been done regarding

this particular outcome. However, rising health costs are a

grave concern in the US, and if teen-motherhood is asso-

ciated with poorer health outcomes in later life, then

increases in teen birthrates may have important conse-

quences to society in terms of the greater health needs and

costs in future decades.

P. H. Patel (&) � B. Sen Department of Healthcare Organization & Policy,

University of Alabama at Birmingham, Birmingham, AL, USA

e-mail: payal@uab.edu

B. Sen

e-mail: bsen@uab.edu


Matern Child Health J (2012) 16:1063–1071

DOI 10.1007/s10995-011-0829-2


It is fairly well established in the social science literature

that experiencing teen-motherhood is associated with sub-

sequent adverse life outcomes for women. Several studies

find strong associations between teen-motherhood and poor

education, underemployment, and lower socioeconomic

status for women [4–11]. British teenage mothers had a

significantly higher level of depression in medium term

postpartum compared to older mothers [10]. Additionally,

teen-mothers often face stigmatization and criticism for

contributing to adult poverty [8].

While experiencing teen-motherhood is correlated with

adverse outcomes, it is also fairly well-established that

experiencing teen-motherhood in itself can be a manifes-

tation of poor socioeconomic status (SES) during child-

hood, as well as a combination of household factors,

environmental stressors, and psychological factors [6, 7,

12–14]. Teen-mothers also exhibit lower cognitive scores

than their counterparts [15] and score higher on the Dean

Romanticism Scale [16] suggesting that they may have

more naı̈ve beliefs about romantic love and the perma-

nency of relationships.

While teen childbearing is found to have a strong

association with a variety of subsequent adverse outcomes

in women, teen childbearing itself seems to be predicted by

a variety of negative childhood experiences, family back-

ground characteristics, and personal psychological factors.

Thus, it remains unclear whether it is experiencing teen-

motherhood per se that leads to the subsequent poor out-

comes, or whether these outcomes are more a result of the

same underlying factors that predict teen-motherhood in

the first place. It is important from a policy perspective that

this be better analyzed. If the poor educational, economic

and health outcomes can be attributed to experiencing teen-

motherhood per se, then resources directly targeted towards

preventing teen-motherhood will benefit the women.

However, if the poor outcomes are more a result of the

underlying factors predicting teen-motherhood per se, then

merely preventing the latter may not yield the expected

improvements in outcomes for these women. Thus, the

challenge for researchers is to decipher whether outcomes

for teen-mothers differ from their counterparts who had

virtually identical familial, environmental and personal

characteristics, but who happened not to become teen-


Researchers have attempted to address this through a

variety of methods. One approach is to include as com-

prehensive a set of control variables as data permits for

childhood and family background. Studies have examined

the outcomes of teenage mothers while controlling for

various background characteristics and have shown that the

association between teenage motherhood and subsequent

outcomes were reduced [17, 18].

Another approach is to find an appropriate ‘control’

group likely to have circumstances very similar to teen-

mothers, but simply not experiencing the actual event of

teen-motherhood themselves. This allows researchers to

infer whether differences in outcomes between the control

group and teen-mothers are attributable to teen childbear-

ing per se [19]. Sisters of teen-mothers who were raised in

the same household (thus, presumably, experiencing the

same household and environmental stressors) but did not

experience a teenage birth are one favored control group

[20–22]. Another control group is teenagers who had

become pregnant but did not actually experience a birth


Very little research currently exists on the association of

teen-motherhood with long-term health outcomes. With

this article, we help fill that gap. We use data from the

NLSY79, and derivations of some of the methods estab-

lished in the literature to help control for underlying con-

founders that may both lead to teenage births and

subsequent poor health outcomes. We describe further

details of the data used in the study below.

Data and Methods

National Longitudinal Survey of Youth 1979

The NLSY79 is a nationally representative sample com-

prised of 12,686 young people aged 14–22 years old on the

date they were first surveyed in 1979, and who were

residing in the US. The respondents were interviewed

annually from 1979 through 1994. After 1994, the survey

was conducted biennially. The NLSY79 initially comprised

of three subsamples:

(1) A cross-sectional sample (n = 6,111) designed to

represent non-institutionalized civilian youths aged

14–22 years.

(2) A supplemental sample (n = 5,295) that oversampled

blacks, Hispanics, and poor Non-black Non-Hispanics

aged 14–22 years.

(3) A military sub-sample (n = 1,280) representative of

the population who enlisted in an active military

branch by September 30, 1978 aged 17–21 years by


Due to funding constraints, the military subsample and

the poor Non-black Non-Hispanic respondents in the sup-

plemental sample were subsequently dropped from the


1064 Matern Child Health J (2012) 16:1063–1071


Outcome Variables

Beginning in survey year 1998, an extended Health module

was created to accurately assess the occurrence of chronic

health problems in the aging NLSY79 cohort. It was

administered to NLSY79 respondents in the first survey

they took after reaching age 40. This occurred anywhere

from 1998 to 2006, depending on the respondents’ year of

birth. We use the physical and mental health components

of the SF-12 Health Survey in the NLSY79 Health module

The SF-12, which stands for ‘‘short-form 12-question’’, is a

brief inventory of self-reported mental and physical health

using twelve standardized questions. The health concepts

include physical functioning, role functioning physical,

general health, bodily pain, social functioning, vitality, role

functioning emotional, and mental health (ALSFRS, 2009).

The exact questions and the distributions of responses in

our sample are in Table 1. Results of the SF-12 are sum-

marized in terms of two meta-scores in the NLSY79

dataset, the Physical Component Summary (PCS) and the

Mental Component Summary (MCS). Scores are created in

NLSY79 according to the manual by Ware et al. [23],

though the precise scoring formula is kept confidential.

These meta-scores are our main outcomes of interest.

Higher scores represent better health.

The PCS and MCS scores were designed such that the

representative US population mean scores are 50, and the

standard deviations 10. Thus each one-point difference

above and below 50 corresponds to one-tenth of a standard-

deviation (ALSFRS, 2009). Because the US population

mean score includes the elderly for whom scores decline

rapidly, a better comparison for the NLSY79 sample might

be the scores for the sub-group of US populations aged

35–44 years, for whom the mean PCS and MCS scores,

respectively, are 52.18 (std. dev. 7.30) and 50.1 (std. dev.


Analytical Approach

The participants in this study include 4,271 NLSY79

female respondents for whom PCS and MCS scores were

reported by 2006. Our primary group of interest is women

who had a live birth as a teenager (‘‘teen-mother’’). When

comparing PCS and MCS scores for teen mothers with

other women in a multivariate regression framework, we

attempt to control for underlying confounders that may

predict both teen-motherhood and future health outcomes

using the following tactics. First, we control for an exten-

sive array of measured familial, demographic and envi-

ronmental characteristics available in the NLSY79 dataset

(described later under ‘‘other variables’’). Next, we attempt

to identify women who are likely to share unmeasured

characteristics with teen-mothers, but who do not actually

become teen-mothers. We consider two comparison

groups: (1) women who became pregnant as teenagers but

then experienced a miscarriage, abortion, or stillbirth

(‘‘teen-pregnancy-only’’); and (2) women who reported

unprotected sexual activity as a teenager, but did not

experience a teen-pregnancy (‘‘teen-unprotected-sex’’). We

identify respondents in the teen-mothers, teen-pregnancy-

only and teen-unprotected-sex groups using information

from the NLSY79 Fertility module, which informs on

contraceptive use and pregnancy outcomes. Specific fer-

tility variables, including age of first (and subsequent)

pregnancies and outcomes of these pregnancies were added

to the NLSY79 beginning in 1984. We use information

from the 1984, 1985 and 1986 surveys to identify the

groups as described below.


We use ‘‘age 18 or less’’ to define a teenager. Therefore,

respondents who meet this criterion for ‘‘age of pregnancy’’

are identified. In 1984, a majority of respondents were

already past the age of 18, in which case our identification

is based on information provided retrospectively. If in 1984

the respondent reports a past pregnancy where age of

pregnancy is 18 or younger, and the outcome of the

pregnancy is a live birth, then they are identified as a ‘teen-

mother’. For respondents 18 years or younger and cur-

rently pregnant in 1984 (1985), data from survey year 1985

(1986) are used to identify the outcome of the pregnancy. If

it is a live birth, then they are also identified as a ‘teen-

mother’. Otherwise the variable is set to 0. Finally, all

responses are compared across the 3 years for consistency.

This procedure results in 1,310 respondents qualifying as

‘teen-mothers’ for our analysis. These numbers are con-

sistent with Hotz et al. [3].


This group includes respondents who experienced a first

pregnancy at age 18 or less, but it ended in a miscarriage,

abortion, or stillbirth, and they did not experience a sub-

sequent pregnancy ending in live birth while still a teen-

ager. Again, 1984, 1985, and 1986 interview data were

used to identify the occurrence and outcomes of the teen

pregnancy. This procedure resulted in 467 women quali-

fying for this group. Of them, 129 respondents reported

having a miscarriage, 320 respondents reported having an

abortion, and 18 respondents reported having a stillbirth as

a teenager. It is important to note that data on abortions,

miscarriages, and pregnancies in NLSY79 interview data

are based on self-reports, and it is also fairly well-estab-

lished that the numbers of abortions among the young is

highly underreported [24]. We speculate that some of the

Matern Child Health J (2012) 16:1063–1071 1065


reported ‘miscarriages’ are likely to have been abortions,

and that some teen pregnancies would have been termi-

nated via abortion if they did not happen to end in a mis-

carriage. Thus, we avoid the approach by Hotz et al. [3] of

only using information on women who report a miscar-

riage. Instead, we combine women who report a miscar-

riage/stillbirth as a teenager with those who report an

abortion as a teenager in one group.


This group includes respondents who report engaging in

non-contraceptive sexual activity as a teenager, but did not

experience a pregnancy. We argue that this is a useful

comparison group to teen-mothers, because their unmea-

sured personal and environmental characteristics lead them

to engage in the risky behavior that leads to teen-mother-

hood, and it is likely a matter of chance that they did not

become pregnant. The Fertility module in NLSY79 pro-

vides specific contraceptive related questions. Specifically,

the respondents identifying themselves as ‘‘not using con-

traception, sexually active’’ when 18 years and under were

included in this group. This procedure resulted in 238

respondents reporting non-contraceptive sexual activity

(another 1,480 respondents reported sexual activity with

contraception, but we do not consider them an appropriate

comparison group). Again, the usual caveats exist about

misreporting in self-reported, retrospective data.

We acknowledge that our comparison groups are unli-

kely to have the identical unmeasured characteristics to

teen-mothers. For example, respondents in the teen-

Table 1 SF-12 questions and distributions in the sample

Question Frequency (N) Percentage (%)

Assessment of general health

Excellent 1,782 21.1

Very Good 3,204 37.9

Good 2,350 27.8

Fair 895 10.6

Poor 219 2.6

Does health limit moderate activities?

Yes, limited a lot 367 4.3

Yes, limited a little 516 6.1

No, not limited at all 7,570 89.6

Does health limit climbing stairs?

Yes, limited a lot 455 5.4

Yes, limited a little 703 8.3

No, not limited at all 7,293 86.3

Have accomplished less than would like in past 4 weeks?

Yes 1,053 12.5

No 7,395 87.5

Does health limit kind of work or other activities?

Yes 917 10.9

No 7,530 89.1

Emotional problems caused to accomplish less in past 4 weeks?

Yes 888 10.5

No 7,559 89.5

Emotional problems made actions less careful?

Yes 728 8.6

No 7,714 91.4

Pain interfered with normal work in past 4 weeks?

Not at all 6,186 73.2

A little bit 1,243 14.7

Moderately 432 5.1

Quite a bit 371 4.4

Extremely 215 2.5

How often felt calm and peaceful in past 4 weeks?

All the time 1,471 17.4

Most of the time 3,635 43.1

A good bit of the time 1,262 14.9

Some of the time 1,320 15.6

A little of the time 538 6.4

None of the time 216 2.6

How often had a lot of energy in past 4 weeks?

All the time 1,493 17.7

Most of the time 3,590 42.5

A good bit of the time 1,169 13.8

Some of the time 1,433 17.0

A little of the time 484 5.7

None of the time 273 3.2

How often felt down-hearted and blue in past 4 weeks?

All the time 134 1.6

Table 1 continued

Question Frequency (N) Percentage (%)

Most of the time 247 2.9

A good bit of the time 193 2.3

Some of the time 1,242 14.7

A little of the time 1,924 22.8

None of the time 4,703 55.7

Physical/Emotional problems interfere with social activities in past

4 weeks?

All the time 153 1.8

Most of the time 216 2.6

A good bit of the time 148 1.8

Some of the time 560 6.6

A little of the time 646 1.7

None of the time 6,717 79.6

Summarized results from the SF-12 scores are given in the NLSY79

dataset as the Physical Component Summary (PCS) and Mental

Component Summary (MCS) scores. Scores are computed based on

algorithms in the manual by Ware et al. [23], but the precise formula

is kept confidential

1066 Matern Child Health J (2012) 16:1063–1071


unprotected sex group may have timed the sexual inter-

course more carefully to avoid pregnancy,—which could

suggest differences in cognitive ability or in the desire to

get pregnant between them and teen-mothers. Some teen-

pregnancy-only respondents may have chosen an abortion

or induced a miscarriage because they wanted to avoid the

socio-economic consequences of teen-motherhood. Abor-

tions and miscarriages may also be more indicative of

experiencing sexual assault and having worse access to

prenatal care, respectively. compared to teen-mothers.

However, while the unmeasured personal and environ-

mental characteristics may not be identical across the

groups, they are likely to have a number of similarities.

Taken in conjunction with a list of measureable charac-

teristics we also control for other variables, which are listed

below. We believe our approach allows us to minimize the

effects of confounders when analyzing the association of

teen-motherhood with future health outcomes.

Other Variables

In our multivariate regression framework, we control for

several measureable demographic, familial and other

background characteristics that are available in the

NLSY79 that may be associated with teen-motherhood and

the outcome of interest in our study. These include race-

ethnicity, region of residence, whether the teenager lived

with both parents at age 14, two proxy variables to control

for the extent reading and learning were encouraged in the

home, the number of siblings, highest grade completed by

respondent’s mother, self-reported bad health in 1979,

poverty status prior to 1979, if parents were alcoholics,

and if the respondents themselves reported substance-use

before age 14.


All statistical analyses were conducted using STATA,

version 11.0. Table 2 illustrates the mean, and standard

deviations for our outcome variables, as well as for the

other demographic, familial and other background char-

acteristics available in the NLSY79. The average PCS and

MCS among teen-mothers were 49.91 and 50.89, respec-

tively, while for all women they were 50.79 and 51.10,

respectively. Notably, while teen-mothers have lower PCS

and MCS compared to other women, they also have several

other differences in their background characteristics com-

pared to other women. For example, teen-mothers are less

likely than counterparts to be living with both parents at

age 14 (54% vs. 63%), more likely to belong to a minority

group, and much more likely to be in poverty prior to 1979

(49% vs. 19%).

Table 3 presents the results of t-tests with unequal vari-

ances to test the equality of mean physical and mental scores

for three categories. The first column compares PCS and

MCS for teen-mothers to all other women. The second col-

umn compares teen-mothers to teen-pregnancy only. The

Table 2 Means and standard deviations of key variables


(N = 1,310)

All other women

(N = 2,961)

Obs Mean SD Obs Mean SD

PCS 959 49.91 (9.62) 186 50.79 (9.04)

MCS 959 50.89 (9.92) 186 51.10 (9.91)

Hispanic 959 0.22 (0.46) 186 0.17 (0.42)

Black 959 0.46 (0.50) 186 0.30 (0.46)

Non-black/Non-Hispanic 959 0.32 (0.47) 186 0.53 (0.50)

Lived with both parents at age 14 959 0.54 (0.50) 186 0.63 (0.48)

Newspaper in household growing upa 952 0.61 (0.49) 185 0.76 (0.43)

Library card in household growing upa 954 0.60 (0.49) 185 0.72 (0.45)

In poverty before 1979 920 0.45 (0.50) 179 0.19 (0.39)

Alcoholic parents 959 0.18 (0.38) 186 0.16 (0.37)

Number of siblings 958 3.56 (2.47) 185 3.15 (2.21)

Highest grade completed 896 11.52 (2.90) 181 11.75 (2.82)

Bad health in 1979 959 0.04 (0.21) 186 0.05 (0.23)

Alcohol at age 14 or younger 959 0.08 (0.27) 186 0.15 (0.35)

Marijuana at age 14 or younger 959 0.06 (0.23) 186 0.06 (0.24)

a These variables serve as proxy variables for the extent to which reading and learning were encouraged in the household where the respondent

grew up

Matern Child Health J (2012) 16:1063–1071 1067


last column compares teen-mothers to teen-unprotected-sex.

These simple bivariate analyses reject the null hypothesis of

equality of means for PCS in all cases. Thus, teen-mothers

appear to exhibit poorer PCS later in life compared to all

women, but also compared to women who had a pregnancy

but not a live birth as a teen, or engaged in unprotected sex as

a teen. However, while we reject the null of equality of means

for MCS between teen-mothers and all other women, we do

not find any statistical differences between the teen-mothers

and the teen-pregnancy only groups, and only a weak sta-

tistical difference (significant at 10% but not 5%) between

the teen-mothers and teen-unprotected-sex group.

Table 4 presents results from three sets of multivariate

Ordinary Least Squares (OLS) regressions (referred to as

OLS Regression 1, 2 and 3 respectively) with PCS and MCS

as the outcome variable. Regression 1 includes a binary

measure for teen-mothers, with all other women being the

comparison group or omitted category, and it only controls

for the age at which PCS and MCS scores were measured.

Regression 2 extends Regression 1 by controlling for the

full set of variables listed under ‘other variables’. This allows

us to inspect how teen mothers differ from all other women in

their PCS and MCS scores after accounting for differences in

measureable demographic, familial and other background

characteristics. Regression 3 adds in separate binary mea-

sures for teen-pregnancy-only and teen-unprotected-sex in

addition to the binary measure for teen-mothers, with the

omitted category now being women not in any of these

groups. This allows us to inspect whether the association

between teen-motherhood (compared to the omitted-cate-

gory) and PCS and MCS are statistically different from the

associations between the other two groups (compared to the

base-category) and these outcomes.

When interpreting the magnitudes of the estimated

results, it is useful to remember that a 1 point reduction in

the PCS or MCS score is equivalent to a one-tenth of one

(population) standard-deviation reduction.

Regression 1 results show teen mothers have lower PCS

(b = -2.095, P \ 0.01) and lower MCS (b = -1.336, P \ 0.01) scores compared to all other women. Regres- sion 2 results show that, when the other demographic,

familial and other background characteristics are controlled

for, the estimated reductions in PCS (b = -1.596, P \ 0.01) and MCS (b = -0.903, P \ 0.01) for teen mothers compared to all other women are smaller, but still

highly significant. Regression 3 results show that, compared

to the omitted-category, teen mothers have significantly

lower PCS (b = -1.590, P \ 0.01) and MCS (b = -1.065, P \ 0.01). In contrast, neither the teen-pregnant-only nor teen-unprotected-sex respondents have PCS that are statis-

tically different than the omitted category. However, in case

of MCS, while the teen-unprotected-sex group is not statis-

tically different from the omitted category, the teen-preg-

nancy-only group shows statistically lower MCS compared

to the omitted category (b = 1.379, P \ 0.01), with the magnitude of the negative association being even greater

than the teen-mothers group. In an F-test, we failed to reject

the null hypothesis that teen-mothers and teen-pregnancy-

only groups are equivalent in terms of reductions in MCS.

Discussion and Conclusion

Extant literature has explored whether teen-motherhood is

linked to outcomes such as educational attainment, or

employment, poverty and welfare dependency in early

Table 3 T-test statistics with unequal variances

Variable PCS score

Mean (Group 1, Group2)

(t statistic)

MCS Score

Mean (Group 1, Group2)

(t statistic)

Teen-mothers (Group1)

compared to All other women (Group 2)

49.82, 51.85

(5.85)c 50.89, 52.20


Teen-mothers (Group 1)

compared to teen-pregnancy-only (Group 2)

49.79, 51.08

(2.09)b 50.89, 51.12


Teen-mothers (Group 1)

compared to Teen-unprotected-sex (Group 2)

49.82, 51.73

(3.57)c 50.90, 51.87


Teen-mother group includes teenagers who had a live birth at age 18 or younger (N = 1,310)

Teen-pregnancy only includes teenagers who had a pregnancy but resulted in an abortion, miscarriage, or stillbirth at age 18 or younger

(N = 467)

Teen-unprotected-sex group includes teenagers who engaged in sexual activity at age 18 or younger but did not experience teen pregnancy

(N = 238) a Significant at the P \ 0.10 level b Significant at the P \ 0.05 level c Significant at the P \ 0.01 level

1068 Matern Child Health J (2012) 16:1063–1071


Table 4 Results of multivariate ordinary least square regression analysis

Variable name Regression 1 Regression 2 Regression 3


b (t stat)


b (t stat)


b (t stat)


b (t stat)


b (t stat)


b (t stat)

Teen-mother -2.095c












Teen-pregnancy only -0.652




Teen unprotected sex 0.309




Age when MCS, PCS score computed 0.115a












Black -1.275c








Hispanic -0.574








Not in SMSA 0.571








SMSA not central city 0.687








SMSA central city 0.455








Region (North central) -0.631








Region (South) -0.393








Region (West) 0.877a








Poverty status when young -0.569








Drink before 14 years -1.941c








Smoke before 14 years -0.168








Marijuana before 14 years -1.557a








Bad health condition -4.888c








Highest grade completed -0.004








Newspaper in household 0.815b








Library card in household 0.205








Lived with both parents at age 14 0.796b








Matern Child Health J (2012) 16:1063–1071 1069


adulthood. To our knowledge, this is the first study to

examine whether teen-motherhood has long term conse-

quences in terms of women’s physical and mental health

later in life.

We find significant and negative associations between

teen-motherhood and women’s physical and mental health

in their 40 s as measured by the Physical Component

Summary and Mental Component Summary meta-scores

from NLSY79 Health module. Our approach involves

using regression models that control extensively for mea-

sured background factors, and also comparing teen-moth-

ers with women at a very high risk of experiencing teen-

motherhood—specifically, women who experienced a teen

pregnancy but not a live birth, and women who had

unprotected sex as a teen but chanced not to get pregnant.

The motivation is to investigate whether it is teen-moth-

erhood per se that leads to adverse health outcomes, or

whether the adverse outcomes are a function of measured

and unmeasured factors that increase the likelihood for


Our results strongly suggest that teen-motherhood does,

indeed, lead to poorer physical health in later life. While

further research is needed to verify exactly why this hap-

pens, we speculate that perhaps the economic conse-

quences of teen-motherhood as well as the stresses of

childrearing at a young age leave these women with fewer

resources to invest in their own physical health. These

results suggest that resources devoted to reducing teen-

motherhood may lead to health cost savings in future


Results regarding mental health are more challenging.

Both teen-motherhood and teen pregnancies not ending in a

live birth have significant and statistically similar negative

associations with future mental health. This may indicate

that it is not teen-motherhood per se, but the unmeasured

factors leading to a teen pregnancy, that actually lead to

worse mental health. It may also indicate that experiencing

a teen pregnancy per se has a negative effect on mental

health, regardless of whether the pregnancy results in a live

birth, and that a pregnancy ending in a non-live birth may

be worse for mental health than those ending in live

births—which is similar to what another set of researchers

found using similar data [25].

We acknowledge several shortcomings of this study.

There are the usual concerns regarding accuracy in self-

reported data, particularly given the sensitive nature of issues

like pregnancy outcomes. We do not have information on

some crucial factors that may predict teen pregnancy out-

comes as well as subsequent health, such as experiences with

sexual abuse and rape. Such factors have been found to be

associated with women having abortions and also suffering

from anxiety/depression and may help explain why mental

health outcomes were more negative for the teen-pregnancy-

only group compared to teen-mothers in our sample [26, 27].

We also lack information on health insurance status and

access to pre-natal care among the teens in our sample.

Finally, as acknowledged previously, there is good reason to

believe that the teen-mothers and our two comparison groups

are not identical in terms of their unmeasured characteristics.

Therefore, there may remain other unmeasured confounders,

hence even for physical health outcomes we must use caution

before interpreting our results as being ‘causal’.

This paper also suggests that more research needs to be

done on the long-term consequences of teen-motherhood.

Table 4 continued

Variable name Regression 1 Regression 2 Regression 3


b (t stat)


b (t stat)


b (t stat)


b (t stat)


b (t stat)


b (t stat)

Number of siblings 0.0628








Tee-mother group includes teenagers who had a live birth at age 18 or younger

Teen-pregnancy-only group includes teenagers who had a pregnancy but resulted in an abortion, miscarriage, or stillbirth at age 18 or younger

Teen-unprotected-sex group includes teenagers who engaged in sexual activity at age 18 or younger but did not experience a teen pregnancy

Comparison group (or omitted-category) in Regressions 1 and 2 are all women who did not become teen mothers.

Comparison group (or omitted-category) in Regression 3 is all women who neither became teen mothers, nor experienced a teen pregnancy, nor

had unprotected sex as a teen

Race: reference group = Non-Hispanic white

SMSA: reference group = SMSA central city not known

Region: reference group = East a Significant at the P \ 0.10 level b Significant at the P \ 0.05 level c Significant at the P \ 0.01 level

1070 Matern Child Health J (2012) 16:1063–1071


The NLSY79 Health module provides a rich array of health

information beyond the SF-12, which permits further

research into the association of teen-motherhood with dif-

ferent health-outcomes. Finally, longitudinal information is

also available the children of the female respondents of

NLSY79, which provide a rich resource for comparing

outcomes of the children of teen-mothers to the children of

their counterparts, to understand whether the effects of

teen-motherhood persist across generations.


1. Darroch, J. E., Singh, S., & Frost, J. J. (2001). Differences in

teenage pregnancy rates among five developed countries: The

roles of sexual activity and contraceptive use. Family Planning Perspectives, 33(6), 244–250.

2. Guttmacher Institute (2010). US Teenage pregnancies, births, and

abortions: National and State Trends and Trends by Race and

Ethnicity. Retrieved from www.guttmacher.org.

3. Hotz, V. J., McElroy, S. W., & Sanders, S. G. (2005). Teenage

childbearing and its life cycle consequences. The Journal of Human Resources, XL (3), 683–715.

4. Maynard, R. A. (1997). The study, the context, and the findings in

brief in Kids Having Kids: Economic costs and social conse-

quences of teen pregnancy. In R. A. Maynard (Ed.), Kids having kids (pp. 4–17). Washington, DC: Urban Institute Press.

5. Hofferth, S. L., Reid, L., & Mott, F. L. (2001). The effects of

early childbearing on schooling over time. Family Planning Perspectives, 33(6), 259–267.

6. Haldre, K., Rahu, K., & Karro, H. (2009). Individual and familial

factors associated with teenage pregnancy: An interview study.

European Journal of Public Health, 19(3), 266–270. 7. Kirby, D. (2001). Emerging answers: Research findings on pro-

grams to reduce teen pregnancy. Washington, DC: National Campaign to Prevent Teen Pregnancy.

8. Lee, J. (2004). Pregnant and parenting teens and poverty. Woman View, 8(5), 1–2.

9. Vernon, M. E., Green, J. A., & Frothingham, T. E. (1983).

Teenage pregnancy: A prospective study of self-esteem and other

sociodemographic factors. Pediatrics, 72(5), 632–635. 10. Liao, T. F. (2003). Mental health, teenge motherhood, and age at

first birth among British women in the 1990s. Working papers of the institute for social and economic research, 2003–2033.

11. Gaudie, J., Mitrou, F., Lawrence, D., Stanly, F., Silburn, S., &

Zubrick, S. (2010). Antecedents of teenage pregnancy from a

14-year follow-up study using data linkage. BMC Public Health, 10, 1–11.

12. East, P. L. (1996). Do adolescent pregnancy and childbearing

affect younger siblings? Family Planning Perspectives, 28(4), 148–153.

13. East, P. L. (1996). The younger sisters of childbearing adoles-

cents: Their attitudes, expectations, and behaviors. Child Devel- opment, 67, 267–282.

14. Woodward, L., Fergusson, D. M., & Horwood, L. J. (2001). Risk

factors and life processes associated with teenage pregnancy:

Results of a prospective study from birth to 20 years. Journal of Marriage and Family, 63, 1170–1184.

15. Shearer, D. L., Mulvihill, B. A., Klerman, L. V., Wallander, J. L.,

Hovinga, M. E., & Redden, D. T. (2002). Association of early

childbearing and low cognitive ability. Perspectives on Sexual and Reproductive Heatlh, 34(5), 236–243.

16. Medora, N. P., & Hellen, C. V. (1997). Romanticism and self-

esteem among teen-mothers. Adolescence, 32(128), 811–824. 17. Duncan, G. J., & Hoffman, S. D. (1990). Teenage welfare receipt

and subsequent dependence among black adolescent mothers.

Family Planning Perspectives, 22, 16–35. 18. Sanders, S., Smith, J., & Zhang, Y. (2007). Teenage childbearing

and maternal schooling outcomes: Evidence from matching. University of Maryland.

19. Hoffman, S. D. (1998). Teenage childbearing is not so bad after

all…Or is it? A review of the new literature. Family Planning Perspectives, 30(5), 236–243.

20. Geronimus, A. T., & Korenman, S. (1992). The socioeconomic

consequences of teen childbearing reconsidered. The Quarterly Journal of Economics, 107(4), 1187–1214.

21. Hoffman, S. D., Foster, E. M., & Furstenberg, F. F. (1993).

Reevaluating the costs of teenage childbearing. Demography, 30(1), 1–13.

22. Concoran, M. E., & Kunz, J. P. (1997). Do unmarried births

among African-American teens lead to adult poverty? Social Service Review, 71(2), 274–287.

23. Ware, J. E., Kosinski, M., & Keller, S. D. (1995). Physical and mental health summary scales (2nd ed.). Boston, MA: The Health Institute, New England Medical Center.

24. Jones, E. F., & Forrest, J. D. (1992). Underreporting of Abortion

in Surveys of US Women: 1976 to 1988. Demography, 29(1), 113–126.

25. Cougle, J. R., Reardon, D. C., & Coleman, P. K. (2005). Gen-

eralized anxiety following unintended pregnancies resolved

through childbirth and abortion: A cohort study of the 1995

National Survey of Family Growth. Journal of Anxiety Disorders, 19, 137–142.

26. Russo, N. F., & Denious, J. E. (2001). Violence in the lives of

women having abortions: Implications for public policy and

practice. Professional Psychology: Research and Practice, 32, 142–150.

27. Steinberg, J. R., & Russo, N. F. (2008). Abortion and anxiety:

What’s the relationship? Social Science and Medicine, 67, 238–252.

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