Associations between social media use, body mass index, and body image among pregnant women

Abstract

Backround

Body image during pregnancy is an important psychosocial factor that influences maternal well-being. Emerging evidence suggests that both social media exposure and body mass index (BMI) may shape body image perceptions during this period. This study examined the associations between social media use, BMI, and body image in pregnant women.

Methods

This cross-sectional, descriptive, and correlational study was conducted with 272 pregnant women recruited through convenience sampling from the gynecology and obstetrics outpatient clinics of a state hospital in the Mediterranean region of Türkiye. Data were collected using a Personal Information Form, the Social Media Addiction Scale–Adult Form, and the Body Image in Pregnancy Scale.

Results

Correlation analysis showed that higher social media addiction scores were significantly associated with higher BIPS scores (r = 0.366, p < 0.001), whereas BMI was not significantly correlated (r = 0.090, p = 0.140) with body image Multiple linear regression analysis further demonstrated that satisfaction with body before pregnancy (β = 0.137, p = 0.024), satisfaction with body changes during pregnancy (β = 0.205, p = 0.003), emotions when away from social media (β = 0.161, p = 0.016), and social media addiction (β = 0.347, p = 0.001) were significantly associated with higher negative body image scores, while worry about postpartum body appearance was inversely associated with BIPS scores (β = -0.155, p = 0.026). The model explained 30.5% of the variance in body image, with social media addiction emerging as the strongest predictor.

Conclusion

This study demonstrated that higher levels of social media use and addiction were associated with more negative body image perceptions among pregnant women. Health professionals may consider integrating counseling and educational interventions into prenatal care to promote healthier and more mindful social media use during pregnancy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-026-04259-8.

Introduction

Pregnancy is a period marked by profound biological, psychological, and emotional changes, during which significant alterations in body shape and appearance occur [1, 2]. Common visible changes include breast enlargement, skin hyperpigmentation, postural adaptations, and the progressive enlargement of the abdomen [1, 3]. Although gestational weight gain is a natural and necessary component of a healthy pregnancy, it may cause some women to feel dissatisfaction with their bodies and negatively affect their body image [4–8]. In fact, pregnancy has consistently been identified as a period of increased vulnerability to negative body image perceptions [4–7, 9]. In recent years, the widespread use of social media has emerged as an additional factor influencing women’s perceptions of their bodies [1, 10–12]. While social media can facilitate social connection and health-related information sharing [10], it simultaneously promotes unrealistic and highly curated beauty ideals. According to social comparison theory, individuals tend to evaluate their own appearance by comparing themselves with others, especially when exposed to idealized and unattainable images [13–15]. This comparison process is intensified on visually oriented platforms where edited, filtered, and idealized images are frequently presented as normative [16–18]. During pregnancy, when the body is already undergoing rapid and uncontrollable transformation, exposure to depictions of “ideal” pregnant bodies—often characterized by minimal weight gain, flawless skin, and a socially celebrated baby bump—can intensify body dissatisfaction [11]. A growing body of evidence indicates that social media exposure is significantly associated with body image concerns among pregnant and postpartum women. A systematic review demonstrated that social media use is linked to increased perceptions of body dissatisfaction, as well as heightened levels of stress, anxiety, depression, and insecurity in this population [19]. Recent studies have also reported that higher pre-pregnancy BMI and greater gestational weight gain are associated with more negative body image perceptions during pregnancy, suggesting that BMI may interact with media exposure to shape self-perception. Furthermore, increases in body image disturbance during pregnancy have been associated with maladaptive eating behaviors, inappropriate gestational weight management, lower birth weight, and reduced breastfeeding self-efficacy, posing potential risks to both maternal and fetal health [2, 11, 20–22]. In Türkiye, as in many Middle Eastern societies, body image during pregnancy is shaped not only by biological changes but also by strong sociocultural expectations. Dominant beauty ideals frequently emphasize thinness and the rapid return to a pre-pregnancy body shape after childbirth [20]. When these cultural norms intersect with intensified social media exposure, pregnant women may experience increased pressure, body dissatisfaction, and negative self-perception [21, 22]. Despite growing recognition of these dynamics, empirical research examining the combined influence of social media use and body mass index (BMI) on body image among pregnant women, particularly in the Turkish context, remains limited. Therefore, this study aimed to examine the associations between social media use, BMI, and body image among pregnant women. We hypothesized that higher levels of social media use and higher BMI would be associated with greater body image dissatisfaction.

Materials and method

Study design and setting

This cross-sectional, descriptive, and correlational study was conducted between November 20, 2023 and March 31, 2024 in the gynecology and obstetrics outpatient clinics of Osmaniye Public Hospital (Mediterranean Region, Türkiye). By design, temporal precedence cannot be established and causal inference is precluded; accordingly, all estimates are interpreted as associations rather than causal effects.

Population, sampling, and sample size

The target population of the study consisted of pregnant women attending the gynecology and obstetrics outpatient clinics of Osmaniye Public Hospital. A non-probability convenience sampling method was used. To minimize selection bias as much as possible within this sampling approach, all pregnant women who visited the outpatient clinics during the data collection period and met the inclusion criteria were consecutively invited to participate on a voluntary basis. Participants who agreed to take part in the study signed an informed consent form prior to data collection. The minimum required sample size was calculated using G*Power 3.1.9.7 software. Based on a significance level of 0.05, a power of 0.95, and an effect size of 0.39—determined according to findings from previous comparable studies [23], the minimum sample size was calculated as 141 participants. In an effort to increase the representativeness and statistical power of the study, a final sample size approximately 90% larger than the calculated minimum was targeted in order to increase the representativeness and statistical robustness of the sample [24]. Accordingly, the study was completed with 272 pregnant women who met the inclusion criteria and agreed to participate. Although efforts were made to include participants across all trimesters, the majority of the sample consisted of women in the third trimester of pregnancy. This predominance may have influenced the distribution of body image scores limit the generalizability of the findings to women in earlier stages of pregnancy and should be considered when interpreting the results.

Eligibility criteria

The criteria for inclusion in the study were being a pregnant woman carrying a healthy fetus, having used social media for a minimum of one year, and being between 18 and 45 years old. The exclusion criteria included high risk pregnancy and suffering from any metabolic, chronic, or psychiatric illness.

Data collection

Potential participants were approached in the outpatient waiting area, and their eligibility was assessed according to the inclusion and exclusion criteria. After obtaining written informed consent, data collection forms were administered face-to-face by the researcher in a private room within the clinic while the participants awaited their examination. Completion of the forms took approximately 20–25 min per participant, and all forms were checked for completeness prior to data entry. The data were collected using a Personal Information Form, the Social Media Addiction Scale—Adult Form (SMAS-AF), and the Body Image in Pregnancy Scale (BIPS).

Personal information form

The form that the researchers prepared by making use of the relevant literature consisted of 29 questions on the descriptive characteristics of the participants (e.g., age, education level, income level, gravidity), characteristics related to the appearance of their body changing during pregnancy (e.g., BMI before pregnancy, caring about weight gained during pregnancy, being satisfied with the appearance of one’s body, being disturbed by the weight gained during pregnancy), and social media usage characteristics (e.g., emotions when away from social media) [9, 11, 19, 25]. BMI values were determined based on the self-reported weight and height of the participants before pregnancy. In addition to standardized scales, custom items related to body changes during pregnancy and social media use were included. For example, the item ‘Emotions when away from social media’ was coded as: 1 = Cannot stay away, 2 = Feel bad, 3 = Feel lonely, and 4 = No problem. The complete wording and coding of all custom items are provided in Appendix 1. In addition, social media use was operationalized and quantified through structured items asking participants to report their average daily duration of use (in hours), the frequency of checking their accounts, the main platforms used (e.g., Instagram, TikTok, Facebook), and the predominant type of content viewed (e.g., pregnancy-related, lifestyle, or appearance-focused content).

Social Media Addiction Scale—Adult Form (SMAS-AF)

The SMAS-AF was developed by Şahin and Yağcı (2017) to assess social media addiction levels in adults aged 18–60 years [26]. It is a 5-point Likert-type scale consisting of 20 items, with total scores ranging from 20 to 100. Items 5 and 11 are reversely scored. Social media addiction levels were categorized according to the established SMAS-AF cut-off points. Higher total scores indicate greater levels of social media addiction (20–35 = not addicted, 36–41 = mildly addicted, 42–57 = moderately addicted, 58–73 = highly addicted, 74–100 = very highly addicted). The original Cronbach’s alpha coefficient was reported as 0.94 [26]. In this study, Cronbach’s alpha coefficient for the scale was calculated as 0.93.

Body Image in Pregnancy Scale (BIPS)

The BIPS was developed by Watson et al. (2017) to measure pregnant women’s perceptions of physical and mental changes in their body [27]. The scale was adapted to Turkish culture by Gün Kakaşçı et al. (2022) [28]. The BIPS is a 5-point Likert-type scale with 34 items (items 1–12 rated from “1 = I strongly disagree” to “5 = I strongly agree”, items 13–29 rated from “1 = I am quite satisfied” to “5 = I am not satisfied at all”, items 30–34 rated from “1 = I never did” to “5 = I always did”). Items 8, 9, 10, 11, and 12 are scored in reverse. A high total BIPS score indicates that the pregnant woman has a highly negative body image. The overall Cronbach’s alpha coefficient for the BIPS was reported as 0.90 BIPS [27, 28]. In this study, the Cronbach’s alpha coefficient for the BIPS was calculated as 0.87.

Variables

The dependent variable of the study was the BIPS score. The primary independent variables were social media use (assessed by the SMAS-AF and selected items from the Personal Information Form related to frequency of use, average daily duration, and dominant content type) and BMI. Additional independent variables included participants’ sociodemographic characteristics and pregnancy-related factors associated with changing body image during pregnancy. BMI values were calculated based on self-reported pre-pregnancy weight and height. Sociodemographic and pregnancy-related variables, including age, education level, income, parity, pregnancy planning status, and gestational age, were treated as covariates in the multiple linear regression analysis.

Statistical analysis

The data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 22.0. The normality of the data was assessed using skewness and kurtosis coefficients (± 2). In addition, assumptions of homogeneity of variance and homoscedasticity were evaluated prior to conducting parametric analyses. First, descriptive statistics (frequency, percentage, mean, and standard deviation) were calculated. As the BIPS scores met the assumptions for parametric testing, the independent-samples t-test was used for comparisons between two independent groups, and one-way ANOVA was applied for comparisons among more than two groups. Tukey’s post hoc test was conducted to determine which groups differed significantly. When the assumption of homogeneity of variance was violated, the Kruskal–Wallis H test was used instead, and pairwise comparisons were performed to identify significant differences between groups. Pearson correlation analysis was performed to examine bivariate associations between BIPS scores and study variables, and correlation coefficients with corresponding p-values were reported. A multiple linear regression analysis was conducted to identify predictors of BIPS scores. In addition to variables that were significant in the bivariate analyses, key covariates including age, education, income, parity, pregnancy planning status, and gestational age were included in the model. Regression diagnostics were performed, including assessments of linearity, residuals, homoscedasticity, influential cases, and multicollinearity (VIF). A two-tailed p-value of < 0.05 was considered statistically significant.

Ethical statement

Ethical approval was obtained from Osmaniye Korkut Ata University Health Sciences Research Ethics Committee (Approval No: 2023/6/7, Date: 02.10.2023), and written permission was received from Osmaniye Public Hospital (Approval No: E-77378720–774.99–229,455,034, Date: 16.11.2023). All participants were informed about the study and provided written informed consent prior to data collection. To ensure privacy, all data were anonymized before analysis.

Results

The mean age of the participants was 28.18 ± 5.95 years. Overall, 29.8% of the women were high school graduates, and 70.6% reported that their income levels were equivalent to their expenses. The mean number of pregnancies was 2.64 ± 1.66, the mean number of births was 1.66 ± 1.47, and the mean number of miscarriages was 0.28 ± 0.74. The mean gestational age was 34.40 ± 7.66 weeks. Regarding trimester distribution, 3.7% of the participants were in the first trimester, 7.7% in the second trimester, and 88.6% in the third trimester. Additionally, 72.4% of the women reported that their pregnancy was planned.

In this study, pre-pregnancy BMI was used for classification because BMI during pregnancy is not a clinically valid measure due to physiological weight gain. Participants were categorized according to the World Health Organization (WHO) BMI classification. As shown in Table 1, the majority of women were within the normal BMI range prior to pregnancy. A notable proportion reported dissatisfaction with their pre-pregnancy body appearance, discomfort with pregnancy-related weight gain and body changes, experiences of negative feedback, and concerns that these changes might reduce spousal attraction.

Table 1.

Body image and social media use characteristics during pregnancy (N = 272)

Variables	n (%)
BMI
Underweight (< 18.5)	18 (6.6)
Normal weight (18.5–24.9)	168 (61.8)
Overweight (25–29.9)	70 (25.7)
Obese (≥ 30)	16 (5.9)
Cared about weight before pregnancy
Yes	147 (54.0)
No	125 (46.0)
Satisfied with body before pregnancy
Yes	216 (79.4)
No	56 (20.6)
Disturbed by weight gain during pregnancy
Yes	76 (27.9)
No	196 (72.1)
Satisfied with body changes during pregnancy
Yes	179 (65.8)
No	93 (34.2)
Receiving negative feedback on body changes
Yes	71 (26.1)
No	201 (73.9)
Worried about spousal attraction
Yes	84 (30.9)
No	188 (69.1)
Worried about postpartum body
Yes	108 (39.7)
No	164 (60.3)
Ideal body image
Slim/slender	37 (13.6)
Normal	215 (79.1)
Slightly overweight	18 (6.6)
Overweight	2 (0.7)
Checks social media after waking up
Yes	157 (57.7)
No	115 (42.3)
Spends time on social media before bed
Yes	198 (72.8)
No	74 (27.2)
Emotions when away from social media
Cannot stay away	37 (13.6)
Feel bad	64 (23.5)
Feel lonely	35 (12.9)
No problem	136 (50.0)
Body satisfaction affected by images
Feel bad/not good enough	56 (20.6)
Satisfied with body	119 (43.7)
No effect	97 (35.7)
Uses filters while on social media
Yes	139 (51.1)
No	133 (48.9)
Follows appearance-related recommendations
Yes	95 (34.9)
No	177 (65.1)
Social media addiction
Not addicted	36 (13.2)
Mild	31 (11.4)
Moderate	133 (48.9)
High	70 (25.7)
Very high	2 (0.7)

BMI Body Mass Index

Patterns of social media use are also presented in Table 1. Many participants reported checking social media immediately after waking and before going to bed, engaging with appearance-related content, using filters, and following appearance-based suggestions. Additionally, nearly half of the sample demonstrated at least a moderate level of social media addiction (Table 1).

The participants who were dissatisfied with their body before pregnancy, those disturbed by weight gain, those dissatisfied with body changes, those receiving negative feedback, those worried about spousal attraction, those worried about postpartum body appearance, and those perceiving slimness as ideal showed significantly different BIPS scores (p < 0.05) (Table 2).

Table 2.

Comparisons of BIPS scores based on body image-related characteristics (N = 272)

Variables	BIPS* Mean ± SD	Test and p-value	Effect sizes
BMI**
Underweight (< 18.5)	74.11 ± 10.69	KW = 6.787	η2 = 0.014
Normal weight (18.5–24.9)	79.11 ± 16.51	p = 0.079
Overweight (25–29.9)	82.87 ± 16.44
Obese (≥ 30)	78.00 ± 15.93
Cared about weight before pregnancy
Yes	77.92 ± 15.65	t = −1.953	d = −0.238
No	81.76 ± 16.69	p = 0.052
Satisfied with body before pregnancy
Yes	77.28 ± 15.80	t = −5.011	d = −0.751
No	88.96 ± 14.51	p = 0.001
Disturbed by the weight gain during pregnancy
Yes	88.50 ± 16.20	t = 5.918	d = 0.800
No	76.27 ± 14.92	p = 0.001
Satisfied with body changes during pregnancy
Yes	74.56 ± 14.44	t = −8.026	d = −1.031
No	89.54 ± 14.69	p = 0.001
Received negative feedback on body changes
Yes	83.76 ± 15.55	t = 2.484	d = 0.344
No	78.24 ± 16.24	p = 0.014
Worried about spousal attraction
Yes	87.36 ± 17.07	t = 5.493	d = 0.721
No	76.25 ± 14.61	p = 0.001
Worried about postpartum body
Yes	86.33 ± 16.40	t = 1.321	d = 0.719
No	75.31 ± 14.57	p = 0.001
Ideal body image
Slim/slender1	86.18 ± 21.04	KW = 7.848	η2 = 0.018
Normal2	78.53 ± 15.18	p = 0.049
Slightly overweight3	80.66 ± 13.94	1 > 2***
Overweight4	74.50 ± 28.99

BIPS Body Image in Pregnancy Scale, *Mean BIPS score: 79.68 ± 16.24 (min: 38, max:128), **BMI categories were defined according to World Health Organization (WHO) criteria, BMI: Body Mass Index, d: Cohen’s d, η²: Eta squared, KW: Kruskal–Wallis H test, SD: Standard Deviation, t: Independent-samples t-test, ***Pairwise comparisons

Similarly, the participants who checked social media after waking up, those who used it before bed, those who felt lonely when away from social media, those who felt bad when exposed to body-related images, those who used filters, those who followed appearance-related suggestions (p = 0.001), and those who were highly addicted showed significantly different BIPS scores (p < 0.05) (Table 3).

Table 3.

Comparisons of BIPS scores based on social media usage characteristics (N = 272)

Variables	BIPS Mean ± SD	Test and p-value	Effect sizes
Checks social media after waking up
Yes	82.73 ± 15.74	t = 3.708	d = 0.455
No	75.52 ± 16.00	p = 0.001
Spends time on social media before bed
Yes	81.09 ± 15.80	t = 2.362	d = 0.322
No	75.91 ± 16.84	p = 0.019
Emotions when away from social media
Cannot stay away 1	82.86 ± 15.89	F = 2.823	η2 = 0.031
Feel bad 2	79.06 ± 16.06	p = 0.039
Feel lonely 3	85.54 ± 11.81
No problem 4	77.61 ± 17.00	3 > 4**
Body satisfaction affected by images
Feel bad/not good enough 1	90.28 ± 17.02	F = 19.708	η2 = 0.128
Satisfied with body 2	74.81 ± 14.68	p = 0.001
No effect 3	79.54 ± 14.73	1 > 2, 1 > 3**
Uses filters on social media
Yes	81.62 ± 16.60	t = 2.026	d = 0.246
No	77.66 ± 15.62	p = 0.044
Follows appearance-related recommendations
Yes	84.15 ± 16.47	t = 3.393	d = 0.432
No	77.28 ± 15.61	p = 0.001
Social media addiction status #
Not addicted 1	69.05 ± 20.76
Mild 2	74.16 ± 13.02	KW = 32.411	η2 = 0.106
Moderate 3	79.33 ± 13.70	p = 0.001
High 4	88.17 ± 15.34	4 > 1, 4 > 3***
Very high 5	83.00 ± 4.24

BIPS: Body Image in Pregnancy Scale, d: Cohen’s d, η²: Eta squared, F: One-way ANOVA, KW: Kruskal–Wallis H test, SD: Standard Deviation, SMAS-AF: Social Media Addiction Scale—Adult Form, t: Independent-samples t-test, ^# Mean SMAS-AF score: 48.41 ± 11.59 (min: 22, max: 78), ** Tukey’s test as a post-hoc test, ***Pairwise comparisons

The correlation analysis showed that higher social media addiction scores were significantly associated with higher BIPS scores (r = 0.366, p < 0.001), whereas BMI was not significantly correlated with BIPS scores (r = 0.090, p > 0.05) (Table 4).

Table 4.

Correlations between BIPS scores and study variables (N = 272)

Variable	r	p
Age	0.042	0.488
Education	−0.049	0.420
Income	−0.009	0.881
Parity	0.016	0.792
Gestational age	0.072	0.239
Pregnancy planning status	0.058	0.344
BMI	0.090	0.140
Satisfaction with body before pregnancy	0.292	< 0.001
Being disturbed by pregnancy weight gain	−0.339	< 0.001
Satisfaction with body changes	0.439	< 0.001
Receiving negative feedback	−0.149	0.014
Worrying about spousal attraction	−0.317	< 0.001
Worrying about postpartum appearance	−0.333	< 0.001
Ideal body image	−0.116	0.057
Checking social media after waking	−0.220	< 0.001
Spending time on social media before bed	−0.142	0.019
Emotions when away from social media	−0.096	0.115
Body satisfaction affected by images	−0.188	0.002
Using filters on social media	−0.122	0.044
Following appearance-related recommendations	−0.202	0.001
Social media addiction status	0.366	< 0.001

BIPS Body Image in Pregnancy Scale, BMI Body Mass Index, r: Pearson correlation coefficient

A multiple linear regression analysis was conducted to identify the independent predictors of BIPS scores. The model included both the variables that were statistically significant in the bivariate analyses and key confounders such as age, education, income, parity, pregnancy planning status, and gestational age. The multiple linear regression analysis results showed that satisfaction with before pregnancy body appearance (β = 0.137), satisfaction with body changes (β = 0.205), worry about postpartum appearance (β = −0.155), emotions when away from social media (β = 0.161), and social media addiction (β = 0.347) were significantly associated with BIPS scores, explaining 30.5% of the total variance in this variable (p < 0.05) (Table 5, Fig. 1).

Table 5.

Multiple linear regression analysis on risk factors and BIPS^¥ scores (N = 272)

BIPS risk factors	B	SE	β	t	p	95%Confidence Interval
Age	0.211	0.194	0.77	1.083	0.280	−0.172–0.593
Education	−1.138	0.823	−0.085	−1.383	0.168	−2.758–0.482
Income	0.553	1.726	0.018	0.320	0.749	−2.847–3.953
Parity	−1.519	0.734	−0.156	−2.070	0.039	−2.963—0.074
Gestational age	0.040	0.115	0.019	0.350	0.727	−0.186–0.266
Pregnancy planning status	2.051	2.086	0.057	0.983	0.326	−2.058–6.160
Satisfaction with body before pregnancy	5.507	2.427	0.137	2.269	0.024	0.726–10.287
Being disturbed by the weight gain during pregnancy	−2.959	2.427	0.137	2.269	0.220	−7.701 – 1.783
Satisfaction with body changes during pregnancy	6.991	2.291	0.205	3.051	0.003	2.478–11.503
Receiving negative feedback on body changes	0.074	2.143	0.002	0.035	0.972	−4.147 – 4.295
Worrying about spousal attraction	−1.728	2.519	−0.049	−0.686	0.493	−6.690 – 3.233
Worrying about postpartum body	−5.140	2.302	−0.155	−2.233	0.026	−9.673 – −0.607
Ideal body image	−1.949	1.880	−0.058	−1.037	0.301	−5.652 – 1.753
Checking social media after waking up	−1.297	2.232	−0.040	−0.581	0.764	−4.944 – 3.637
Spending time on social media before bed	−1.870	2.136	−0.051	−0.875	0.382	−6.077 – 2.338
Emotions when away from social media	2.305	0.949	0.161	2.428	0.016	0.436–4.175
Body satisfaction affected by images	0.065	1.343	0.003	0.048	0.961	−2.580 – 2.710
Using filters on social media	2.208	2.135	0.068	1.034	0.302	−1.996 – 6.412
Following appearance-related recommendations	0.523	2.192	0.015	0.238	0.562	−5.693 – 3.099
Social media addiction status	5.857	1.053	0.347	5.560	0.001	3.783–7.932

Model summary: R = 0.597, R² = 0.356, Adj. R² = 0.305, F (20, 251) = 6.944, p = 0.001

Diagnostics: Residuals were normally distributed (Std. Residual range: −2.7 to + 3.4) Homoscedasticity was met. No influential outliers were detected (Cook’s Distance < 0.06) Multicollinearity was not a concern (VIF values = 1.1–2.2)

^*Multiple linear regression, ^¥ BIPS: Body Image in Pregnancy Scale

Fig. 1.

Graphical representation of the multiple linear regression analysis results on risk factors associated with pregnant women’s Body Image in Pregnancy Scale (BIPS) scores. Positive coefficients indicate higher BIPS scores, reflecting a more negative body image. Red dots represent statistically significant predictors (p < 0.05) that have a noteworthy influence on pregnant women’s body image. BIPS: Body Image in Pregnancy Scale

Discussion

This study examined the associations between social media use, BMI, and body image among pregnant women. Dissatisfaction with body appearance before pregnancy, dissatisfaction with changes during pregnancy, concern about postpartum appearance, negative emotions when away from social media, and higher levels of social media addiction were significantly associated with higher BIPS scores. The regression model explained 30.5% of the variance in body image. After adjusting for age, education, income, parity, pregnancy planning status, and gestational age, only dissatisfaction with bodily changes during pregnancy, concern about postpartum appearance, and parity remained significant predictors. Importantly, the observed associations remained significant even after controlling for key confounding factors using multiple regression analysis.

The finding that BMI was not associated with body image contrasts with several prior studies that found higher BMI to be linked with more negative body image [8, 12, 29, 30], although some studies have similarly reported no association [31, 32]. The discrepancy may stem from sample characteristics, trimester distribution, and cultural context. In this study, the majority of participants were in the third trimester (mean gestational age = 34 weeks), when weight gain is expected and may be perceived as normative. Limited BMI variability in the sample may also have reduced the likelihood of detecting significant associations. Body image perceptions during pregnancy are also influenced by sociocultural expectations. In Turkish society, as in many Middle Eastern cultures, thinness and rapid return to pre-pregnancy weight are highly valued. Such norms may shape women’s perceptions more strongly than objective BMI. Evidence from East Asian and Western contexts similarly indicates that cultural expectations moderate the relationship between BMI and body image [20, 33, 34], suggesting that cultural frameworks are crucial for interpreting cross-population differences. Evidence from India also indicates that pregnant women’s body image is shaped by cultural and social norms, with third-trimester women reporting heightened concerns about appearance [29]. These results align with the cultural influences observed in our study population. Consistent with previous research, dissatisfaction with body changes and concerns about postpartum appearance were associated with more negative body image, aligning with findings from Japanese and Western samples [35]. These findings are consistent with recent research showing that social media exposure—especially through highly visual platforms such as Instagram—is associated with increased body dissatisfaction during pregnancy. A 2025 study conducted in Türkiye found that upward social comparison on Instagram was significantly associated with more negative body image among pregnant women [36].

Similarly, a recent latent profile analysis identified distinct patterns of body image among pregnant women, emphasizing the role of psychological and social factors [12]. Social media addiction was also strongly associated with higher BIPS scores. Although causal mechanisms could not be established, theoretical frameworks such as social comparison theory suggest that exposure to idealized images may facilitate upward comparison and internalization of unrealistic beauty ideals [13, 14]. Furthermore, sociocultural pressures—including societal expectations regarding rapid postpartum body ‘recovery’—have been shown to be associated with increased body image dissatisfaction and poorer psychological well-being in the perinatal period [37]. This reinforces the possibility that cultural ideals and societal expectations may interact with social media use and be linked to more negative body perceptions. Platforms like Instagram may further reinforce these processes through visually curated content. Systematic reviews support that increased exposure to idealized images is associated with greater body dissatisfaction among pregnant and postpartum women [1, 10, 11, 36]. However, these relationships are correlational and should not be interpreted as evidence that social media use directly causes negative body image.

In this context, BMI and social media exposure may operate synergistically and be jointly associated with variations in body image during pregnancy. Although BMI alone was not a significant predictor in the present study, women with higher or rapidly changing body weight may be more vulnerable to negative self-evaluations when exposed to idealized or unrealistic body standards on social media. Psychological theories such as social comparison theory, self-objectification theory, and thin-ideal internalization suggest that women do not interpret bodily changes in isolation, but rather through comparison with culturally promoted ideals. Thus, even when weight gain is within a physiologically normal range for pregnancy, frequent exposure to curated and idealized online images has been associated with higher levels of body dissatisfaction, particularly among women who perceive their bodies as deviating from socially valued norms. Importantly, reverse causation is also possible: women who already experience body dissatisfaction may engage more frequently with social media or seek appearance-focused content, thereby reinforcing negative self-perceptions. For example, women who feel dissatisfied with their bodies may be more inclined to seek out, compare themselves to, or avoid certain types of appearance-focused content on social media, which may further shape their body image perceptions.

Taken together, these findings underscore that body image in pregnancy is shaped by both cultural and social forces. In Türkiye, where social expectations emphasize both maternal well-being and aesthetic ideals, the interaction between sociocultural context, body changes, and digital influences may be particularly important. This suggests that caution is needed when generalizing findings across different populations and highlights the need for cross-cultural research to clarify universal versus culturally specific patterns. These findings should therefore be interpreted within the specific sociocultural context of Türkiye, where norms regarding pregnancy, beauty, and motherhood may differ from those in other societies.

The present findings offer important implications for both clinical practice and public health interventions during pregnancy. First, they highlight the necessity of incorporating routine body image screening into prenatal care. Simple, validated tools such as the BIPS can be used by midwives and nurses to identify women at risk for body image dissatisfaction and associated psychological distress. Early identification would allow for targeted counseling and appropriate referral to mental health support when necessary. Secondly, prenatal education programs should be updated to include structured content on normal physiological body changes in pregnancy, helping women distinguish between healthy, expected changes and socially constructed beauty ideals. Providing evidence-based information on gestational weight gain, body diversity, and postpartum body variability can reduce unrealistic expectations and promote body acceptance.

In addition, the strong association between social media use and negative body image underscores the importance of media literacy interventions as part of antenatal education. Educational sessions could focus on helping women critically evaluate online content, recognize image manipulation, and understand the selective and idealized nature of social media portrayals. Teaching strategies such as limiting exposure to appearance-focused accounts, curating positive content, and engaging in mindful social media use may reduce the harmful effects of upward social comparison.

From a public health perspective, these findings support the development of digitally delivered, culturally sensitive campaigns that promote positive body image during pregnancy. Community-based programs, mobile applications, and web-based resources could be designed to deliver supportive messages, normalize bodily changes, and challenge unrealistic post-pregnancy body expectations. Such initiatives may be particularly impactful in societies where sociocultural and aesthetic pressures regarding motherhood and physical appearance are high.

Overall, integrating body image education and digital literacy skills into maternal health services may not only improve maternal psychological well-being but also strengthen maternal–infant bonding, reduce antenatal anxiety, and contribute to healthier long-term outcomes for both mother and child.

This study also had certain limitations. First, the cross-sectional, descriptive, and correlational design restricts causal inference, meaning that no cause-and-effect relationships can be established between the studied variables. Because data were collected at a single point in time, the temporal order between exposures (e.g., social media use, BMI) and outcomes (body image perceptions) cannot be determined. Therefore, the findings should be interpreted as associations only, not as causal relationships. Future longitudinal studies are recommended to clarify the directionality of these associations and to examine whether social media exposure mediates the relationship between BMI and body image in pregnant women. In particular, future research should examine whether social media exposure functions as a mediating pathway through which BMI is linked to body image perceptions during pregnancy. Second, participants were recruited from a single hospital using convenience sampling, which may constrain external validity and limit generalizability to other regions, institutions, and care settings. Women who do not regularly attend antenatal clinics or who experience barriers to accessing healthcare services were not represented in the sample. Third, the reliance on self-reported data raises the possibility of response bias, particularly social desirability bias, as participants may have under- or overreported sensitive issues such as negative body image or problematic social media use. In particular, pre-pregnancy weight was self-reported, which may have introduced recall bias. Additionally, social media engagement was not objectively measured, and the absence of digital tracking (e.g., screen-time data) may have limited the precision of the exposure assessment. Fourth, several important potential confounders, including depression, anxiety, internalized weight stigma, body-related sensitivity, and broader sociocultural influences, were not assessed or controlled for, which may have affected the observed associations. Furthermore, BMI categories may not be fully applicable across different cultural contexts, further limiting the external validity of the findings. Fifth, although the gestational age of participants ranged from 1 to 42 weeks, the majority (88.6%) were in the third trimester, making meaningful trimester-specific comparisons unfeasible. This imbalance should be taken into consideration when interpreting the results. Finally, the regression model explained only 30.5% of the variance in body image, indicating that unmeasured biological, psychological, and social factors likely play a substantial role in shaping body image perceptions during pregnancy.

Conclusion and recommendations

This study found that social media–related factors and body-related concerns, including dissatisfaction with body changes and worry about postpartum appearance, were associated with negative body image perceptions among pregnant women. These patterns of association highlight the need for increased awareness and targeted educational initiatives in prenatal care, while further longitudinal research is required to clarify the direction and causal pathways of these relationships.

In this study, it was found that dissatisfaction with one’s body before pregnancy, worry about postpartum body appearance, feeling lonely when away from social media, and social media addiction were associated with negative body image perceptions in pregnant women. In light of these results, health professionals should be attentive to how pregnant women feel about their bodies and recognize that social media may contribute to body image concerns. Examining body image during pregnancy is important to the health of both the pregnant woman and the baby. Health professionals should assess whether pregnant women are influenced by unrealistic beauty standards on social media, and in this regard, provide training and counseling on topics such as media literacy, critical thinking, and resisting unrealistic visual ideals. Besides, women’s perceptions of their bodies should be routinely evaluated, and counseling should be offered to help them maintain a healthy perspective during pregnancy. Considering the widespread use of social media, initiatives to promote a positive body image via digital platforms may be beneficial. At the public health level, integrating media literacy and supportive counseling into routine prenatal care could help promote a positive body image during pregnancy and support maternal and pediatric health. However, these findings warrant cautious interpretation owing to the study’s cross-sectional design, BMI estimated from self-reported before pregnancy weight, which may introduce recall bias, and single-center recruitment, all of which may constrain causal inference and external validity.

Future studies should adopt longitudinal designs that extend into the postpartum period to clarify the temporal and causal relationships between body mass index, social media use, and body image throughout the perinatal transition. Including multiple assessment points would allow researchers to examine changes in body image over time and identify critical periods of vulnerability. Further research should also incorporate more diverse and representative samples, as well as a broader range of potential confounding variables, such as psychological distress, eating behaviors, and internalized sociocultural ideals. Comparative studies across different sociocultural contexts would be particularly valuable for distinguishing universal patterns from culture-specific influences. In addition, qualitative and mixed-methods approaches could provide deeper insight into women’s subjective experiences, perceptions, and coping strategies related to body image during and after pregnancy.

Abbreviations

BMI

Body Mass Index

SMAS-AF

Social Media Addiction Scale – Adult Form

BIPS

Body Image in Pregnancy Scale

SPSS

Statistical Package for the Social Sciences

ANOVA

One-way analysis of variance

Authors’ contributions

C.A. and F.K.T. designed the study. F.K.T., C.A., and G.N. were responsible for the inclusion of participants, and C.A., F.K.T., and G.N. conducted the interviews. C.A. and F.K.T. conducted the data analysis and wrote the discussion. C.A., F.K.T., and G.N. contributed to the first draft of the article. All authors revised the manuscript and approved the final version.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All expenses associated with this study were covered by the authors.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

Prior to commencing the study, ethical approval was obtained from the Osmaniye Korkut Ata University Health Sciences Research Ethics Committee (Approval No: 2023/6/7, Date: 02.10.2023), and written permission was received from Osmaniye Public Hospital (Approval No: E-77378720–774.99–229455034, Date: 16.11.2023). Before the study, pregnant women were informed about the research procedure, and then, those agreeing to participate in the study submitted an informed consent form. All principles of the Declaration of Helsinki were respected during the research process.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.