Association between intimate partner violence and pregnancy intention: evidence from the Peruvian demographic and health survey
verfasst von:
Brenda Caira-Chuquineyra, Daniel Fernandez-Guzman, Andrea G. Cortez-Soto, Diego Urrunaga-Pastor, Guido Bendezu-Quispe, Carlos J. Toro-Huamanchumo
Intimate partner violence (IPV) in Peru represents a significant public health challenge. IPV can influence women’s reproductive and social behaviors, undermining fertility control, and exacerbating unintended pregnancies. Our objective was to assess the association between IPV and pregnancy intention among Peruvian women of reproductive age.
Methods
We conducted a secondary analysis of Peru’s 2020 Demographic and Family Health Survey data. The independent variable in this study was IPV against women, which includes psychological IPV, sexual IPV, and physical IPV. If a respondent experienced any of these three forms of IPV, the IPV variable was labeled as “yes”; if none were present, it was labeled as “no”. The dependent variable was pregnancy intention (no vs. yes). We utilized a generalized linear model (GLM) from the Poisson family with a log link function to assess the relationship between IPV occurrences (total and each IPV type) and pregnancy intention. We report crude and adjusted prevalence ratios (aPR) with 95% confidence intervals (95%CI).
Results
We analyzed data from 8466 women aged 15 to 49. The prevalence of any IPV was 49.6% (psychological IPV: 45.8%; physical IPV: 22.2%; and sexual IPV: 4.3%). Exposure to physical IPV (aPR: 1.05; 95% CI: 1.03–1.07), psychological IPV (aPR: 1.04; 95% CI: 1.02–1.06), and sexual IPV (aPR: 1.09; 95% CI: 1.04–1.13), as well as a history of any IPV (aPR: 1.05; 95% CI: 1.02–1.07), were associated with a higher probability of not intending to become pregnant. This association persisted after adjusting for confounders like age, marital status, educational attainment, education level of the child’s father, place of residence, wealth, ethnicity, and parity.
Conclusion
One in two Peruvian women reported experiencing IPV. An association was observed between IPV exposure and a higher probability of not holding an intention to become pregnant.
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Abkürzungen
IPV
Intimate partner violence
ENDES
Demographic and family health survey
INEI
National institute of statistics and informatics
STROBE
Strengthening the reporting of observational studies in epidemiology
PNC
Prenatal care
GLM
Generalized linear model
Poisson
Poisson distribution
VIF
Variance inflation factor
cPR
Crude prevalence ratio
aPR
Adjusted prevalence ratio
95% CI
95% confidence interval.
Introduction
Intimate partner violence (IPV) is recognized globally as one of the most prevalent forms of violence against women [1]. It encompasses physical, sexual, and psychological harm inflicted by an intimate partner [2]. Globally, an estimated 27% of women aged between 15 and 49 who have been in a relationship report having experienced physical or sexual violence from a partner.
Beyond the immediate physical and psychological repercussions, IPV can profoundly influence a woman’s reproductive and social behaviors, often undermining fertility control, increasing the risk of unwanted pregnancies, coerced abortions, inadequate pregnancy weight gain, preterm deliveries, low birth weight newborns, reduced breastfeeding duration, and heightened neonatal and perinatal mortality [3‐5]. The ripple effect of IPV extends further, heightening susceptibilities to cardiovascular, respiratory, neurological, and metabolic disorders, as well as predisposing victims to mood disorders, substance abuse, and suicidal tendencies [6, 7]. Some evidence suggests that IPV survivors might prefer preventing pregnancies, leading to increased contraceptive use [8]. However, in unintended pregnancies, some findings report a reduction in psychological and sexual abuse as the pregnancy progresses, indicating a transient respite around childbirth [9]. However, others have documented persistent or escalated abuse, often driven by paternity disputes [10].
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In 2018, South America reported an IPV prevalence of 25%, while estimates for Latin America and the Caribbean varied between 21% and 38% [11]. Specifically, in Peru, 2017 data revealed that 30.6% of women between ages 15 and 49 who were ever married or in cohabitation experienced physical violence, and 6.5% endured sexual violence [12]. Consequently, IPV in Peru is not merely a societal concern but a significant public health challenge, punctuated by alarming rates of abuse and feminicide [13]. This pattern could potentially exacerbate unintended pregnancy rates in a country where abortions, being illegal, frequently occur under dangerous conditions, posing grave health risks to women and sometimes leading to fatalities [14]. While prior research has explored the nexus between IPV and unintended pregnancies among women of reproductive age [15], they often lacked national and only addressed psychological violence—a form of abuse reported as highly prevalent in the region [16]. Therefore, this study aimed to assess the association between IPV experiences and pregnancy intention in the Peruvian context.
Methods
Study design
This study is a secondary data analysis from the Peruvian Demographic and Family Health Survey (ENDES) conducted in 2020. The National Institute of Statistics and Informatics (INEI) develops ENDES to capture the socio-demographic and health attributes of the Peruvian population. Data collection involves direct interviews conducted by trained professionals who visit selected households to complete three distinct questionnaires targeting households, women of childbearing age, and heads of households. More information about ENDES methodology is available in the survey technical report [17].
The present manuscript adheres to the STROBE statement guidelines (Strengthening the Reporting of Observational Studies in Epidemiology) [18].
Population, sample, and sampling
The ENDES is a survey carried out annually with national, urban, and rural representation by the geographical domain (Coast, Sierra, and Jungle) and for the 25 regions of Peru. It employs a two-stage complex probabilistic sampling strategy involving the selection of clusters and then households within them.
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Our study targeted women of childbearing age (15–49 years), excluding those who had not registered a pregnancy in the 5 years preceding the survey and those with incomplete information on the variables of interest (Fig. 1). Thus, the data for analysis include women of childbearing age and their pregnancies in the 5 years leading up to ENDES 2019.
Fig. 1
Flowchart for sample selection
×
Outcome
The outcome was non-intention to become pregnant. Was determined based on the following question: “When you became pregnant, did you want to get pregnant at that moment, did you want to wait longer, or did you not want to have (more) children?” The response options were: “Yes, at that time”, “Yes, but I wanted to wait”, and “I didn’t want to have (more) children”. For this study, women who selected the first response were categorized as having intended to become pregnant. In contrast, those who chose either of the latter two responses were considered as having not intended to become pregnant.
Independent variable
The independent variable was IPV. IPV was measured from seven questions related to physical violence, 10 related to psychological or emotional violence, and two about sexual violence committed against the woman by her partner at some point in their relationship (Supplementary material 1). From the data, we derived three binary variables to assess IPV against women: psychological IPV, sexual IPV, and physical IPV, each denoted as “yes” or “no”. A composite IPV variable was then created, encompassing all three types. If a respondent experienced any of the three IPV forms, the composite IPV was labeled as “yes”; if none were present, it was labeled as “no”.
Other variables
Based on a review of previous studies, we included the following covariates that have been reported to be associated with both variables of interest [8, 19, 20]: mother’s sociodemographic characteristics such as age tertiles (15 to 25 years, 26 to 35, and 36 to 49), current marital status (with a partner and without a partner), education level of the child’s father (initial/preschool/primary, secondary and higher), employment status (works, does not work), geographic region (metropolitan Lima, Costa without Lima, Highlands and Jungle), area of residence (urban and rural), wealth index (first quintile, second quintile, third quintile, fourth quintile, and fifth quintile), ethnicity (mestizo, quechua, negro, and others). Likewise, the father’s education level (initial/preschool/primary, secondary, and higher) was considered. In addition, pregnancy variables such as parity (first child, second child, and third child or more), use of contraceptives prior to pregnancy (no and yes), and the number of prenatal check-ups (PNC) (greater than or equal to six or less than six), as recommended by the Peruvian Ministry of Health [21], were also included. The use of contraceptives before pregnancy and the number of prenatal check-ups were collected for each pregnancy of the surveyed woman, ensuring that the data is not biased by events in other pregnancies.
Statistical analysis
The 2019 ENDES databases were downloaded and imported into the Stata® v.16.0 program (Stata Corporation, College Station, Texas, USA). The analyses considered the complex sampling and the ENDES weighting factors using the Stata “svy” module. Absolute frequencies and weighted proportions were calculated for the descriptive analysis of categorical variables. We evaluated the relationship between the categorical variables using the chi-square test with the Rao-Scott correction for the bivariate analysis. A generalized linear model (GLM) of the Poisson family with a logarithmic link function was performed to evaluate the association between the presence of IPV (any IPV and for each IPV component) and the intention to become pregnant. In this way, we report the crude prevalence ratios (cPR) and adjusted (aPR) with their respective 95% confidence intervals (95%CI). For the adjusted model, we used an epidemiological approach [22], including the following confounding variables: age, marital status, educational level of both parents, residence, wealth, ethnicity, and parity, whose association has been described in previous studies [8, 19, 20].
Multicollinearity was assessed using the variance inflation factor (VIF) to ensure the reliability of our adjusted regression model. Traditionally, a VIF value greater than 10 indicates substantial multicollinearity between predictor variables. Reassuringly, all variables in our model had VIF values below this threshold. The significance level was set at p < 0.05 for all statistical tests.
Results
We analyzed data from 8466 women aged between 15 and 49 who reported at least one pregnancy within the 5 years preceding ENDES 2019 (Fig. 1).
Most participants were aged between 26 and 35 years (36.7%). A majority were in a relationship (89.6%), had achieved secondary education (46.4%), were employed (63.4%), and resided in metropolitan Lima (33.2%). Nearly 48.9% identified as mestizo, and 34.9% had three or more children. Over 90% had attended six or more PNC (Table 1).
Table 1
Characteristics of the study population (n = 8466)
Characteristics
n
%a
IC95%a
Age
15 to 25 years old
2980
33.0
31.5–34.7
26 to 35 years old
3047
36.7
35.1–38.5
36 to 49 years old
2439
30.3
28.4–31.8
Current marital status
With partner
7582
89.6
88.5–90.5
Without partner
884
10.4
9.5–11.5
Women’s education level
Primary or preschool
1648
16.3
15.1–17.6
Secondary
4023
46.4
44.6–48.2
Higher
2795
37.3
35.5–39.1
Education level of the child’s father
Primary or preschool
1253
12.9
11.8–14.0
Secondary
4360
49.6
47.8–51.4
Higher
2853
37.6
35.7–39.4
Employment condition
Yes
5313
63.4
61.7–65.0
No
3153
36.6
35.0–38.3
Geographical region
Lima Metropolitan Area
1145
33.2
31.5–35.0
Rest of coastline
2539
26.0
24.5–27.7
Highlands
2602
24.1
22.4–25.9
Jungle
2180
16.6
15.2–18.0
Residence area
Urban
5954
77.0
75.7–78.3
Rural
2512
23.0
21.7–24.3
Wealth index
First quintile
2285
20.2
18.8–21.7
Second quintile
2247
23.6
22.0–25.2
Third quintile
1740
20.6
19.3–21.9
Fourth quintile
1243
17.4
16.0–18.8
Fifth quintile
951
18.2
16.6–19.9
Ethnicity
Mestizo
3713
48.9
47.2–50.6
Quechua
2279
22.7
21.2–24.2
Negro
893
11.1
10.1–12.2
Others
1581
17.3
16.0–18.8
Parity
First children
2508
31.4
30.2–32.6
Second children
2771
33.7
32.5–35.0
Third children or more
3187
34.9
33.5–36.3
Contraceptive use
No
1721
19.4
18.1–20.7
Yes
6745
80.6
79.3–81.9
Number or Prenatal checkups
> =6
7731
91.1
90.2–92.0
< 6
735
8.9
8.0–9.8
Physical violence
No
6468
77.8
76.5–79.1
Yes
1998
22.2
20.9–23.5
Psychological violence
No
4543
54.2
52.4–55.9
Yes
3923
45.8
44.1–47.6
Sexual violence
No
8090
95.7
95.0–96.2
Yes
376
4.3
3.8–5.0
Intimate partner violence
No
4180
50.4
48.6–52.2
Yes
4286
49.6
47.8–51.4
Pregnancy intention
With intention
3933
47.6
45.8–49.3
Without intention
4533
52.4
50.7–54.2
aWeighted percentages according to survey complex sampling
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The prevalence of psychological, physical, and sexual IPV was 45.8, 22.2, and 4.3%, respectively. A combined IPV prevalence of 49.6% was found, with a higher proportion in women who reported not having a current partner (76.3%; p < 0.001), those with less than a higher education level (52.0–54.0%; p < 0.001), that their partner or ex-partner had an educational level lower than higher education (53.7–53.9%; p < 0.001), those who did not have a labor relationship (52.3%; p < 0.001), who belonged to the second and third quintiles of poverty (55.9 and 53.0%; p < 0.001). Regarding obstetric characteristics, women with three or more children (55.8%; p < 0.001), those who used contraceptives (54.5%; p = 0.004), who had less than six PNC (53.0%; p < 0.001) and those who did not intend to become pregnant (54.6%, p < 0.001), had a higher prevalence of IPV (Table 2).
Table 2
Prevalence of intimate partner violence according to the characteristics of the study population (n = 8466)
Characteristics
Intimate partner violence
No
Yes
p-value**
n
%*
IC95%*
n
%*
IC95%*
Age
15 to 25 years old
1478
49.0
46.3–51.8
1502
51.0
48.2–53.7
0.394
26 to 35 years old
1542
51.9
48.9–54.9
1505
48.1
45.1–51.1
36 to 49 years old
1160
50.0
46.5–53.5
1279
50.0
46.5–53.5
Current marital status
With partner
3997
53.6
51.7–55.4
3585
46.4
44.6–48.3
< 0.001
Without partner
183
23.2
18.8–28.3
701
76.8
71.7–81.2
Women’s education level
Primary or preschool
780
48.0
44.5–51.4
868
52.0
48.6–55.5
< 0.001
Secondary
1881
46.0
43.5–48.5
2142
54.0
51.5–56.5
Higher
1519
56.9
53.7–60.1
1276
43.1
39.9–46.3
Education level of the child’s father
Primary or preschool
580
46.1
41.9–50.1
673
53.9
49.9–58.1
< 0.001
Secondary
2014
46.3
43.9–48.7
2346
53.7
51.3–56.1
Higher
1586
57.2
54.1–60.4
1267
42.8
39.6–45.9
Employment condition
Yes
2484
47.8
45.6–49.9
2829
52.3
50.1–54.4
< 0.001
No
1696
54.9
51.9–57.9
1457
45.1
42.1–48.1
Geographical region
Lima Metropolitan Area
563
52.2
47.9–56.4
582
47.9
43.6–52.1
0.069
Rest of coastline
1272
49.9
47.0–52.8
1267
50.1
47.2–53.0
Highlands
1210
46.8
44.3–49.3
1392
53.2
50.7–55.7
Jungle
1135
52.9
49.7–56.0
1045
47.1
44.0–50.3
Residence area
Urban
2920
50.4
48.2–52.5
3034
49.6
47.5–51.8
0.991
Rural
1260
50.4
47.4–53.4
1252
49.6
46.6–52.6
Wealth index
First quintile
1140
51.0
47.6–54.4
1145
49.0
45.6–52.4
< 0.001
Second quintile
1005
44.1
41.0–47.2
1242
55.9
52.8–59.0
Third quintile
832
47.0
43.5–50.4
908
53.0
49.6–56.5
Fourth quintile
650
50.5
46.4–54.6
593
49.5
45.4–53.6
Fifth quintile
553
61.5
56.1–66.6
398
38.5
33.4–43.9
Ethnicity
Mestizo
1964
52.4
49.7–55.1
1749
47.6
44.9–50.3
0.094
Quechua
1007
47.4
44.0–50.8
1272
52.6
49.2–56.0
Negro
438
49.8
45.2–54.3
455
50.2
45.7–54.8
Others
771
48.9
44.8–53.0
810
51.1
47.0–55.2
Parity
First children
1368
55.2
52.4–58.0
1140
44.8
42.0–47.6
< 0.001
Second children
1424
52.3
49.6–54.9
1347
47.7
45.1–50.4
Third children or more
1388
44.2
41.6–46.9
1799
55.8
53.1–58.4
Contraceptive use
Yes
790
45.5
42.1–48.9
931
54.5
51.1–57.9
0.004
No
3390
51.5
49.5–53.5
3355
48.5
46.5–50.5
Number or prenatal checkups
> =6
3854
50.7
48.9–52.5
3877
49.3
47.5–51.1
< 0.001
< 6
326
47.0
41.9–52.2
409
53.0
47.8–58.1
Pregnancy intention
With intention
2171
55.8
53.3–58.4
1762
44.2
41.6–46.7
< 0.001
Without intention
2009
45.4
42.9–47.9
2524
54.6
52.1–57.1
*Weighted percentages according to survey complex sampling
**Calculated by Chi2 test of independence with Rao Scott correction for complex sampling. P-values < 0.05 are in bold
Over half the participants (52.4%) reported their pregnancy as unintended, with a higher proportion in women aged 15 to 25 years (62.4%; p < 0.001), who reported not having a current partner (61.6%; p < 0.001), those with educational level below higher education (56.0–56.3%; p < 0.001), that their partner or ex-partner had an educational level below higher education (55.0–56.9%; p < 0.001), those who resided in rural areas (57.3%; p < 0.001), who belonged to the first and second quintiles of poverty (59.4 and 58.0%; p < 0.001) and those women with Quechua ethnicity (55.8%; p = 0.026). Regarding obstetric characteristics, women who had less than six PNC (62.2%; p < 0.001) and those who reported physical IPV (61.5%; p < 0.001), psychological IPV (57.6%; p < 0.001), sexual IPV (72.2%; p < 0.001), and those with any IPV (57.7%; p < 0.001), had a higher prevalence of non-intended pregnancy (Table 3).
Table 3
Prevalence of non-intended pregnancy according to the characteristics of the study population (n = 8466)
Characteristics
Intended pregnancy
Intended
Non-intended
p-value**
n
%*
IC95%*
n
%*
IC95%*
Age
15 to 25 years old
1141
37.6
35.0–40.2
1839
62.4
59.8–65.0
< 0.001
26 to 35 years old
1529
51.0
48.2–53.7
1518
49.0
46.3–51.8
36 to 49 years old
1263
54.5
51.0–57.8
1176
45.5
42.2–49.0
Current marital status
With partner
3601
48.7
46.8–50.6
3981
51.3
49.4–53.2
< 0.001
Without partner
332
38.4
33.9–43.1
552
61.6
56.9–66.1
Women’s education level
Primary or preschool
715
44.0
40.5–47.5
933
56.0
52.5–59.5
< 0.001
Secondary
1769
43.7
41.4–46.0
2254
56.3
54.0–58.6
Higher
1449
54.1
50.9–57.2
1346
45.9
42.8–49.1
Education level of the child’s father
Primary or preschool
537
43.1
38.9–47.4
716
56.9
52.6–61.1
< 0.001
Secondary
1930
45.0
42.8–47.2
2430
55.0
52.8–57.2
Higher
1466
52.6
49.4–55.7
1387
47.4
44.3–50.6
Employment condition
Yes
2468
47.4
45.1–49.6
2845
52.6
50.4–54.9
0.711
No
1465
48.0
45.4–50.7
1688
52.0
49.3–54.6
Geographical region
Lima Metropolitan Area
545
50.3
46.4–54.3
600
49.7
45.7–53.6
0.073
Rest of coastline
1213
47.4
44.4–50.3
1326
52.6
49.7–55.6
Highlands
1202
46.6
44.0–49.3
1400
53.4
50.7–56.0
Jungle
973
43.9
40.6–47.2
1207
56.1
52.8–59.4
Residence area
Urban
2876
49.1
47.0–51.2
3078
50.9
48.8–53.0
< 0.001
Rural
1057
42.7
39.7–45.6
1455
57.3
54.4–60.3
Wealth index
First quintile
940
40.6
37.4–44.0
1345
59.4
56.0–62.6
< 0.001
Second quintile
961
42.0
39.0–45.1
1286
58.0
54.9–61.0
Third quintile
858
49.8
46.5–53.2
882
50.2
46.8–53.5
Fourth quintile
639
48.9
44.8–53.0
604
51.1
47.0–55.2
Fifth quintile
535
58.9
53.4–64.1
416
41.1
35.9–46.6
Ethnicity
Mestizo
1807
49.9
47.3–52.5
1906
50.1
47.5–52.7
0.026
Quechua
996
44.2
41.0–47.3
1283
55.8
52.7–59.0
Negro
422
47.6
43.2–52.0
471
52.4
48.0–56.8
Others
708
45.6
41.8–49.5
873
54.4
50.5–58.2
Parity
First children
1228
50.8
48.0–53.6
1280
49.2
46.4–52.0
< 0.001
Second children
1515
55.3
52.8–57.8
1256
44.7
42.2–47.2
Third children or more
1190
37.2
34.6–39.8
1997
62.8
60.2–65.4
Contraceptive use
No
804
47.4
44.2–51.0
917
52.6
49.0–55.8
0.896
Yes
3129
47.6
45.6–49.6
3616
52.4
50.4–54.4
Number or ANC visits
> =6 ANC
3657
48.6
46.8–50.3
4074
51.5
49.7–53.2
< 0.001
< 6 ANC
276
37.8
33.0–42.8
459
62.2
57.2–67.0
Physical violence
No
3182
50.2
48.2–52.2
3286
49.8
47.8–51.8
< 0.001
Yes
751
38.5
35.4–41.6
1247
61.5
58.4–64.6
Psychological violence
No
2325
52.0
49.4–54.6
2218
48.0
45.4–50.6
< 0.001
Yes
1608
42.4
40.1–44.8
2315
57.6
55.2–59.9
Sexual violence
No
3825
48.5
46.7–50.3
4265
51.5
49.7–53.3
< 0.001
Yes
108
27.8
21.9–34.5
268
72.2
65.5–78.1
Intimate partner violence
No
2171
52.8
50.1–55.4
2009
47.2
44.6–49.9
< 0.001
Yes
1762
42.4
40.1–44.6
2524
57.7
55.4–59.9
*Weighted percentages according to survey complex sampling
**Calculated by Chi2 test of independence with Rao Scott correction for complex sampling. P-values < 0.05 are in bold
In the adjusted regression model, after adjusting for potential confounders, having experienced physical IPV (aPR: 1.05; 95% CI: 1.03–1.07), psychological IPV (aPR: 1.04; 95% CI: 1.02–1.06), and sexual IPV (aPR: 1.09; 95% CI: 1.04–1.13), as well as a history of any IPV (aPR: 1.05; 95% CI: 1.02–1.07), were associated with a higher probability of not intending to become pregnant (Table 4).
Table 4
Association between intimate partner violence and non-intended pregnancy, Peru, 2020
Characteristics
Crude Model
Adjusted Modela
cPR
95%CI
p-value
aPR
95%CI
p-value
Intimate partner violence
No
Ref.
Ref.
Yes
1.07
1.05–1.10
< 0.001
1.05
1.02–1.07
< 0.001
Physical violence
No
Ref.
Ref.
Yes
1.08
1.05–1.10
< 0.001
1.05
1.03–1.07
< 0.001
Psychological violence
No
Ref.
Ref.
Yes
1.06
1.04–1.09
< 0.001
1.04
1.02–1.06
0.001
Sexual violence
No
Ref.
Ref.
Yes
1.14
1.09–1.18
< 0.001
1.09
1.04–1.13
< 0.001
Odds ratios and confidence intervals were calculated considering the survey complex sampling. P-values < 0.05 are in bold
cPR crude Prevalence Ratio, aPR adjusted Prevalence Ratio
aModel adjusted by age, marital status, educational level, partner’s educational level, residence, wealth, ethnicity, and parity
Discussion
We sought to assess the association between intimate partner violence and pregnancy intention among childbearing-age women in Peru. Half of the participants had experienced IPV, with psychological IPV being the most prevalent. Additionally, a relationship was found between IPV and pregnancy intention; women who experienced any form of IPV were less likely to intend for pregnancy.
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The prevalence of specific types of IPV in this study contrasts with prior results. For instance, a systematic review from 2017 revealed that Peru had a prevalence of 30.6% for physical IPV and 6.5% for sexual IPV [12], both higher than our current findings. An analysis by INEI of the ENDES data spanning 2009 to 2018 indicated that psychological (73.0 to 58.9%), physical (38.2 to 30.7%), and sexual (8.8 to 6.8%) decreased in this period (any form of IPV: 76.9 to 63.2%) [23]. Tiravanti-Delgado et al.’s 2019 study using the ENDES reported a general IPV prevalence of 57.7%, psychological at 52.8%, physical at 29.5%, and sexual at 7.1%, higher than our results for the same year [24]. Their study had a larger sample of 21,518 women of reproductive age compared to our 8466, which might account for the discrepancies. The diminishing IPV prevalence over the years in Peru is corroborated by our results. This decrease in the IPV may be the cause of a greater awareness of the equal rights of women and the public policies against violence against women by the Peruvian government, such as the National Agreement adopted in 2002 in its policies 7 and 16, the Strategic Plan for National Development in its “Bicentennial Plan: Peru towards 2021” approved by Supreme Decree 054–2011-PCM in its axis 1 and 2, and in the National Policies approved by Supreme Decree 056–2018-PCM in its priority guideline No. 4.6 [25, 26].
Half of the women we evaluated had no intention of becoming pregnant after experiencing IPV, a prevalence higher in rural areas. This is a decrease from a 2012 study, where 62.3% of urban and 74.1% of rural women became unintentionally pregnant [27]. This decreasing trend in unintended pregnancies could be due to enhanced informational campaigns, better contraceptive access, and evolving reproductive aspirations in Peru.
Women exposed to any form of IPV (psychological, physical, or sexual) have a higher prevalence of unwanted pregnancies. This pattern aligns with findings from various countries: Ethiopia [28], Bangladesh [27, 29], Brazil [27, 30], Japan, Nabidia, Samoa, Serbia and Montenegro, Thailand, Tanzania [27], Spain [31], and previous studies in Peru [27]. A likely reason is the dominance exerted by abusive partners, curtailing women’s fertility control and reinforcing submissive dynamics in sexual relations, subsequently leading to unwanted pregnancies [19]. The relationship between unwanted pregnancies and contraceptive use in this context is multifaceted. Some women, fearing further abuse during pregnancy or succumbing to pressures from partners or in-laws, avoid contraceptives altogether [32]. On the other hand, having suffered from violence promotes the use of contraceptive methods to avoid getting pregnant without the partner knowing, the use of emergency contraception in the event of a forced attempt to have sexual intercourse, or opting for abortion in the case of get pregnant without their consent [33]. This clandestine use of abortion is intrinsically linked to IPV: women exposed to violence often report higher abortion rates than those who are not [19]. However, in Peru, these statistics might not reflect reality. Since only therapeutic abortion is legal, many IPV-induced abortions could go unreported in medical records.
The evident link between IPV and unintended pregnancies underscores the need for robust prevention programs against violence directed at women, safeguarding their well-being and reproductive autonomy. Identifying signs of physical, sexual, or psychological violence is critical. Often, women in dependent relationships or those with low self-esteem might downplay or overlook the true extent of the abuse they face [34]. Equally vital is promoting sex education, family planning, and accurate information about contraceptive methods. In Peru, misconceptions persist about different contraceptive options, their usage, and potential side effects. Additionally, local support programs should be prioritized. These initiatives should provide information on IPV and offer guidance on reporting violence and seeking help. Creating an environment that fosters a sense of belonging, acceptance, and destigmatization for victims is essential. Such supportive environments have been shown to correlate with reduced rates of unintended pregnancies among abused women [35].
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This study has some limitations. First, this study is a secondary analysis of a public database, so the accuracy of all the data analyzed cannot be guaranteed. However, the ENDES is a widely used survey with quality controls that allow the study of the health status of the Peruvian population, being used by researchers and authorities to study health problems in the Peruvian context. Second, there may be a social desirability bias on the part of the respondents due to how sensitive it may be to provide information regarding violence issues, which could underestimate the presence of violence in the population studied. Third, due to the survey’s design (cross-sectional study), it is impossible to establish a causal relationship between the variables of interest.
Conclusion
Half of the Peruvian women in our study experienced IPV, with psychological IPV being the most prevalent. Exposure to IPV increases the likelihood of not intending to get pregnant. These findings underscore the urgency of reinforcing Peru’s ongoing preventive measures against IPV and maternal health strategies. Comprehensive sexual education and systematic IPV monitoring are essential to address this concern. Furthermore, it is crucial to inculcate respect and gender equality from an early age.
Statement of experiments on humans/human data
Not applicable.
Statement of informed consent from a legal guardian or legally authorized representative
Not applicable.
Declarations
Ethical approval and consent to participate
This study performed a secondary analysis of a publicly available access database from the INEI (https://proyectos.inei.gob.pe/microdatos/). Importantly, this database omits any identifiers linked to participants, ensuring complete confidentiality. Given the non-identifiable nature of the data and its public availability, seeking additional ethical approval for this analysis was deemed unnecessary. It should be emphasized that during the primary data collection phase, the INEI team had duly obtained informed consent from all respondents.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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