Abstract
Abstract
Objective
To evaluate the association between body composition from early pregnancy to 42 days postpartum and postpartum weight retention (PPWR).
Design
This retrospective cohort study was conducted at Chengdu Shuangliu Maternal and Child Health Care Hospital from June 2020 to December 2021.
Setting
The study was conducted in Sichuan Province, southwestern China.
Participants
A total of 673 pregnant women at 6–13 weeks of gestation were included.
Outcome measures
Demographic and health information of participants was collected from the electronic medical record system using a self-designed questionnaire. Body fat percentage (PBF), fat mass (FM), fat-free mass (FFM), lean mass (LM) and protein were measured using bioelectrical impedance analysis. Logistic regression and restricted cubic spline (RCS) analyses were performed to examine the association between body composition and PPWR.
Results
During early pregnancy, compared with the bottom quartile group, women in the top quartile group of PBF and FM levels had a 51% (95% CI 0.24 to 0.99) and 64% (95% CI 0.17 to 0.76) lower risk of PPWR, respectively. For each SD increase in PBF and FM levels, the risk of PPWR decreased by 29% (95% CI 0.55 to 0.91) and 35% (95% CI 0.50 to 0.85), respectively. In contrast, at 42 days postpartum, for each SD increase in PBF, FM, FFM and LM levels, the PPWR risk elevated by 251% (95% CI 2.70 to 4.62), 315% (95% CI 3.15 to 5.57), 56% (95% CI 1.30 to 1.89), and 71% (95% CI 1.42 to 2.09). RCS analysis revealed that PBF and FM levels during early pregnancy were negatively correlated with the risk of PPWR (p-overall <0.001, p-non-linear=0.444–0.501), while ‘J’-shaped relationships were observed for PBF, FM, FFM and LM levels at 42 days postpartum (p-overall <0.001, p-non-linear=0.306–0.734).
Conclusions
PBF and FM during early pregnancy are negatively associated with PPWR, whereas PBF, FM, FFM and LM at 42 days postpartum show positive associations. Among these, changes in FM contribute the most to PPWR.
Keywords: Body Mass Index, Obesity, Observational Study
STRENGTHS AND LIMITATIONS OF THIS STUDY.
Body composition provides higher precision and accuracy compared with body mass index.
Recall bias and information bias may exist due to the retrospective cohort study design.
Potential confounding bias may persist owing to untested or unknown parameters.
Extrapolation is limited due to the small sample size and study area restrictions.
Introduction
Gestational weight gain in pregnant women is mainly attributed to changes in metabolism and fetal growth and development, and these changes may persist into the postpartum period. The optimal gestational weight gain is determined based on prepregnancy body mass index (BMI).1 Generally, women are expected to return to their prepregnancy weight by the sixth week postpartum. However, several prior studies have shown that more than 20% of women retain a significant portion of the weight gained during pregnancy, even 6 months to 2 years after delivery.2,6 Unlike other periods of weight gain, postpartum weight retention (PPWR) often results in abdominal obesity,7 which not only affects subsequent pregnancies in women of childbearing age,8 but is also associated with nutrition-related metabolic diseases9,12 and offspring health.5 13 14 PPWR may increase the risk of overweight and obesity through mechanisms such as chronic inflammation and insulin resistance.15
Previous studies have shown that the average weight retention is 1.5–5 kg at 6–12 months postpartum.16 PPWR is associated with various factors, such as maternal age, prepregnancy BMI, excessive gestational weight gain, ethnicity, diet, breastfeeding and behavioural factors.17,22 At 1 year postpartum, excessive weight gain during pregnancy pushed 33% of women with normal prepregnancy weight into the overweight or obese category and 44% of overweight women into the obese category.23
Weight gain during pregnancy includes pregnancy-related components (fetus, placenta and amniotic fluid), uterine and breast tissues, maternal body water (both intracellular and extracellular) and adipose tissue. Changes in body composition during pregnancy may contribute to postpartum body weight to varying degrees. However, there are limited reports, both domestically and internationally, on the relationship between body composition (particularly body fat) and PPWR. The aim of this retrospective cohort study was to investigate the associations between body composition from early pregnancy to 42 days postpartum and PPWR.
Methods
Subjects
This retrospective cohort study selected pregnant women at 6–13 weeks of gestation who registered for delivery at Chengdu Shuangliu District Maternal and Child Health Care Hospital from June 2020 to December 2021 through the electronic information system. Women who met the following inclusion criteria were enrolled: (1) aged 18–45 years; (2) single pregnancy; (3) natural conception and (4) planned to breastfeed after delivery. Finally, 719 eligible women were recruited. Of these participants, 46 mothers with the following conditions were excluded: (1) suffered from pre-existing chronic metabolic diseases before pregnancy (n=15), such as hypertension (n=1), dyslipidaemia (n=4), diabetes (n=2), hyperthyroidism (n=1), hypothyroidism (n=5), chronic nephritis (n=1) and cardiovascular diseases (n=1), etc; (2) experienced severe gastrointestinal symptoms, such as diarrhoea and constipation (n=3); (3) reported with infectious diseases (n=5), such as AIDS (n=1), syphilis (n=1), hepatitis B (n=3); (4) took antibiotics and glucocorticoids within the past 3 months (n=8) and (5) had incomplete body composition information (n=15). In total, 673 women aged 18–45 years with single pregnancies were included in our study. A prior study6 indicated that PPWR rate was more than 20%, and for each SD increase in prepregnancy BMI, the risk of PPWR decreased by about 80%. Assuming a 20% loss to follow-up, we calculated using PASS 15.0 software that this study required 656 subjects. Therefore, the sample size of 673 cases in this study is sufficient. Participants were informed of participation in subsequent scientific research during their first obstetric visit, and pregnant women who agreed to participate signed an informed consent form. Informed consent was obtained from all the participants.
Basic information collection
Questionnaire surveys and body indicator measurements were conducted by trained professional doctors and nurses. A self-designed questionnaire was used to collect demographic and medical history information of pregnant women from the electronic medical record system, including maternal age, prepregnancy weight, education level, race, household registration type, smoking status, alcohol consumption, gestational weight gain, pregnancy history (gravidity and parity) and disease history. The heights and weights of the pregnant women were measured using an electronic height and weight scale with an accuracy of 0.1 cm and 0.1 kg, respectively. Prepregnancy BMI was calculated as the ratio of the prepregnancy weight (kg) to squared height (m2). Excessive gestational weight gain was defined according to the ‘Standard of Recommendation for Weight Gain During Pregnancy’.24 According to literature reports,25 PPWR refers to the weight difference between different time points after delivery and prepregnancy weight. In this study, the time point was set at 42 days postpartum; therefore, PPWR was defined as: a difference of more than 5 kg between weight at 42 days postpartum and prepregnancy weight.
Measurement of body composition
Body composition was measured using bioelectrical impedance analysis (NAQ-P, Sihai Huachen, China). Measurements were performed by uniformly trained professional technicians during early pregnancy (at 6–13 weeks of gestation) and 42 days after delivery. Before the measurements, participants were instructed to remove their shoes, socks, outerwear and metal accessories, wear light clothing and stand barefoot on the metal plates of the instrument with feet apart. They were then asked to firmly grip the metal pads with both hands and wait for the detection to complete before reading the data. The percentage of body fat (PBF), fat mass (FM), fat-free mass (FFM), lean mass (LM), protein and basal metabolic rate (BMR) were recorded. Body fat percentage was calculated as the ratio of body fat content to body weight, multiplied by 100%.
Statistical analysis
All statistical analyses were performed using RStudio software V.4.3.0. Descriptive statistics were presented as mean with SE for continuous variables and frequency with percentage for categorical variables. Comparisons among groups were tested using independent sample t-tests and χ2 tests for continuous and categorical variables, respectively. Continuous variables (PBF, FM, FFM, LM) were divided into quartiles, with the lowest quartiles serving as the reference group. Logistic regression analyses were conducted to estimate the ORs and the corresponding 95% CIs for the risk of PBF, FM, FFM and LM. These analyses focused on the period from early pregnancy to 42 days postpartum in relation to PPWR. Model 1 was a univariate analysis without any adjustment. Model 2 included potential confounders such as maternal age, educational level, ethnicity, type of household registration, early pregnancy BMI, gestational weight gain, gravidity and parity. Restricted cubic spline (RCS) analysis with four knots was performed to test the dose–response relationship between body composition levels and PPWR. In our study, 15 participants were lost to follow-up due to incomplete body composition information collection, and 673 pregnant women were finally included in the analysis, with a loss rate of 2.23%, not exceeding 5%. Therefore, this study directly deleted the data of the lost population. A two-tailed p<0.05 was considered statistically significant.
Results
A total of 673 women, aged 27.62±3.88 years, were included in this study (table 1). Mothers classified as having PPWR had a lower prepregnancy BMI (20.91±2.27 vs 22.27±2.89, p<0.001) and BMR (1247±70 vs 1281±79, p<0.001), but higher gestational weight gain (15.77±3.77 vs 11.23±3.84, p<0.001). No significant differences were observed between the two groups in maternal age, ethnicity, type of household registration, education level, smoking status, alcohol consumption, gravidity and parity (p>0.05).
Table 1. Baseline characteristics of 673 participants.
| Variables | Overall (N=673) | Non-PPWR (N1=444) | PPWR (N2=229) | F/χ2 | P value |
|---|---|---|---|---|---|
| Maternal age, years | 27.62 (3.88) | 27.77 (3.86) | 27.32 (3.91) | 2.01 | 0.157 |
| Maternal age (≥35), n (%) | 18 (2.67) | 12 (2.70) | 6 (2.62) | 1.37 | 1.000 |
| Ethnicity (Han), n (%) | 665 (98.81) | 439 (98.87) | 226 (98.69) | 1.97 | 1.000 |
| Household registration type (urban), n (%) | 585 (86.92) | 388 (87.39) | 197 (86.03) | 0.14 | 0.707 |
| Education level, n (%) | 0.54 | 0.763 | |||
| College | 153 (23.04) | 104 (23.69) | 49 (21.78) | ||
| High school | 436 (65.66) | 284 (64.69) | 152 (67.56) | ||
| Primary school | 75 (11.30) | 51 (11.62) | 24 (10.67) | ||
| Smoking status, n (%) | 0.92 | 0.631 | |||
| Never | 241 (38.50) | 164 (39.33) | 77 (36.84) | ||
| Occasionally | 188 (30.03) | 127 (30.46) | 61 (29.19) | ||
| Frequently | 197 (31.47) | 126 (30.22) | 71 (33.97) | ||
| Alcohol consumption, n (%) | 0.98 | 0.614 | |||
| Never | 137 (21.88) | 96 (23.02) | 41 (19.62) | ||
| Occasionally | 444 (70.93) | 292 (70.02) | 152 (72.73) | ||
| Frequently | 45 (7.19) | 29 (6.95) | 16 (7.66) | ||
| Gravidity, n (%) | 0.85 | 0.358 | |||
| ≥3 | 171 (26.80) | 119 (28.07) | 52 (24.30) | ||
| <3 | 502 (73.40) | 325 (71.93) | 177 (75.70) | ||
| Parity, n (%) | 2.29 | 0.130 | |||
| Multiparity | 227 (35.58) | 160 (37.74) | 67 (31.31) | ||
| Primiparity | 446 (64.42) | 284 (62.26) | 162 (68.69) | ||
| Early pregnancy BMI, kg/m2 | 21.81 (2.77) | 22.27 (2.89) | 20.91 (2.27) | 38.15 | <0.001 |
| Early pregnancy BMI, n (%) | 28.35 | <0.001 | |||
| <18.5 | 56 (8.32) | 28 (6.31) | 28 (12.23) | ||
| 18.5–24 | 480 (71.32) | 301 (67.79) | 179 (78.17) | ||
| ≥24 | 137 (20.36) | 115 (25.90) | 22 (9.61) | ||
| GWG, kg | 12.77 (4.38) | 11.23 (3.84) | 15.77 (3.77) | 71.91 | <0.001 |
| Excessive GWG, n (%) | 284 (42.26) | 121 (27.31) | 163 (71.18) | 144.20 | <0.001 |
| BMR (baseline), Kcal | 1270 (77) | 1281 (79) | 1247 (70) | 29.41 | <0.001 |
Data are presented as mean±SD for continuous variables and frequency (%) for categorical variables.
Bold values represent statistically significant differences between groups (P<0.05).
BMI, body mass index; BMR, basal metabolic rate; GWG, gestational weight gain; N, numbers of subject; PPWR, postpartum weight retention.
A comparison of body composition between the PPWR group and the non-PPWR group is presented in table 2. Analysis of variance revealed that, compared with non-PPWR group, PBF, FM, FFM, LM, protein and weight in the PPWR group were lower in early pregnancy but higher at 42 days postpartum, with greater changes in values (p<0.001).
Table 2. Comparison of body composition between PPWR group and non-PPWR group.
| Overall(N=673) | non-PPWR(N1=444) | PPWR(N2=229) | F | P value | |
|---|---|---|---|---|---|
| Early pregnancy | |||||
| PBF, % | 25.36 (4.66) | 26.06 (4.73) | 24.00 (4.20) | 30.89 | <0.001 |
| FM, kg | 14.05 (4.20) | 14.73 (4.32) | 12.73 (3.63) | 35.66 | <0.001 |
| FFM, kg | 40.33 (3.68) | 40.78 (3.72) | 39.45 (3.46) | 20.09 | <0.001 |
| LM, kg | 37.04 (4.11) | 37.51 (4.14) | 36.14 (3.91) | 17.23 | <0.001 |
| Protein, kg | 8.15 (0.90) | 8.25 (0.91) | 7.95 (0.86) | 17.31 | <0.001 |
| Weight, kg | 54.37 (7.15) | 55.50 (7.25) | 52.19 (6.43) | 25.49 | <0.001 |
| 42 days postpartum | |||||
| PBF (postpartum), % | 27.71 (4.61) | 27.00 (4.43) | 29.08 (4.66) | 31.97 | <0.001 |
| FM (postpartum), kg | 16.27 (4.30) | 15.59 (4.06) | 17.58 (4.46) | 33.96 | <0.001 |
| FFM (postpartum), kg | 41.65 (3.76) | 41.37 (3.69) | 42.19 (3.85) | 7.24 | 0.007 |
| LM (postpartum), kg | 38.43 (3.96) | 38.07 (3.91) | 39.12 (3.97) | 10.69 | 0.001 |
| Protein (postpartum), kg | 8.45 (0.87) | 8.38 (0.86) | 8.60 (0.87) | 10.38 | 0.001 |
| Weight (postpartum), kg | 57.92 (6.97) | 56.97 (6.81) | 59.78 (6.92) | 25.49 | <0.001 |
| Change values from early pregnancy to 42 days postpartum | |||||
| PBF change, % | 2.35 (3.96) | 0.94 (3.44) | 5.08 (3.45) | 218.50 | <0.001 |
| FM change, kg | 2.22 (3.06) | 0.87 (2.41) | 4.85 (2.41) | 166.80 | <0.001 |
| FFM change, kg | 1.33 (2.28) | 0.60 (1.97) | 2.74 (2.17) | 411.70 | <0.001 |
| LM change, kg | 1.39 (2.89) | 0.56 (2.62) | 2.98 (2.73) | 125.20 | <0.001 |
| Protein change, kg | 0.31 (0.64) | 0.13 (0.58) | 0.66 (0.60) | 123.70 | <0.001 |
| Weight change, kg | 3.55 (3.82) | 1.46 (2.60) | 7.59 (2.23) | 920.10 | <0.001 |
Data are presented as mean±SD.
Bold values represent statistically significant differences between groups (P<0.05).
FFM, fat-free mass; FM, fat mass; LM, lean mass; N, numbers of subject; PBF, percentage of body fat; PPWR, postpartum weight retention.
As shown in figure 1, PPWR (ie, weight change) was positively correlated with changes in PBF, FM, FFM and LM (r: 0.55–0.80, p<0.001), and with the strongest association observed for FM change (r=0.80). These results indicate that weight gain during pregnancy is characterised by increases in FM and fat-free mass, with a particular emphasis on the accumulation of body fat.
Figure 1. Correlation analysis between body composition from early pregnancy to 42 days postpartum and postpartum weight. Adjusted for early pregnancy BMI, maternal age, ethnicity, household registration type, education level, gravidity, parity, gestational weight gain. BMI, body mass index; FFM, fat-free mass; FM, fat mass; LM, lean mass; PBF, percentage of body fat. *P<0.05, **P<0.01 and ***P<0.001.
Table 3 presents the ORs (95% CI) for PPWR according to body composition levels in the first trimester. After adjusting for maternal age, educational level, ethnicity, type of household registration, early pregnancy BMI, gestational weight gain, gravidity and parity, a negative association between PBF and FM levels and risk of PPWR was identified. Women with PBF and FM levels in the top quartile had a 51% (OR 0.49, 95% CI 0.24 to 0.99) and 64% (OR 0.36, 95% CI 0.17 to 0.76) lower risk of PPWR, respectively, compared with those in the bottom quartile. The risk of PPWR decreased by 29% (OR 0.71, 95% CI 0.55 to 0.91) and 35% (OR 0.65, 95% CI 0.50 to 0.85) for each SD increase in PBF and FM levels, respectively. Additionally, a positive relationship between body composition levels at 42 days postpartum and the risk of PPWR was observed, as shown in table 4.
Table 3. Logistic regression analysis of body composition levels during early pregnancy and postpartum weight retention.
| Quartiles of body composition level | ||||||
|---|---|---|---|---|---|---|
| Variables | Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P for trend | Per 1 SD increase |
| PBF, % | <21.80 | 21.80–25.36 | 25.36–28.90 | >28.90 | ||
| N (case/total) | 76/170 | 64/167 | 54/168 | 35/168 | ||
| Model 1 | Ref. | 0.77 (0.50 to 1.19) | 0.59 (0.38 to 0.91) | 0.33 (0.20 to 0.52) | 0.168 | 0.63 (0.53 to 0.74) |
| Model 2 | Ref. | 1.01 (0.62 to 1.65) | 0.69 (0.41 to 1.17) | 0.49 (0.24 to 0.99) | 0.638 | 0.71 (0.55 to 0.91) |
| FM, kg | <10.60 | 10.60–14.05 | 14.05–17.10 | >17.10 | ||
| N (case/total) | 78/169 | 67/168 | 50/168 | 34/168 | ||
| Model 1 | Ref. | 0.77 (0.50 to 1.19) | 0.49 (0.31 to 0.77) | 0.30 (0.18 to 0.48) | 0.318 | 0.59 (0.49 to 0.71) |
| Model 2 | Ref. | 0.96 (0.58 to 1.58) | 0.70 (0.41 to 1.18) | 0.36 (0.17 to 0.76) | 0.757 | 0.65 (0.50 to 0.85) |
| FFM, kg | <37.90 | 37.90–40.33 | 40.33–42.40 | >42.40 | ||
| N (case/total) | 71/177 | 76/168 | 41/160 | 41/168 | ||
| Model 1 | Ref. | 1.23 (0.80 to 1.89) | 0.51 (0.32 to 0.82) | 0.48 (0.30 to 0.76) | 0.009 | 0.68 (0.57 to 0.81) |
| Model 2 | Ref. | 1.15 (0.72 to 1.82) | 0.70 (0.43 to 1.14) | 0.73 (0.42 to 1.25) | 0.364 | 0.82 (0.67 to 1.00) |
| LM, kg | <34.30 | 34.30–37.04 | 37.04–39.60 | >39.60 | ||
| N (case/total) | 79/177 | 61/167 | 48/162 | 41/167 | ||
| Model 1 | Ref. | 0.71 (0.46 to 1.10) | 0.52 (0.33 to 0.82) | 0.40 (0.25 to 0.64) | 0.154 | 0.70 (0.59 to 0.83) |
| Model 2 | Ref. | 0.77 (0.48 to 1.22) | 0.74 (0.45 to 1.21) | 0.61 (0.35 to 1.07) | 0.311 | 0.87 (0.71 to 1.06) |
Data are presented as ORs with corresponding 95% CIs. ‘P for trend’ is the trend effect value obtained by including body composition quartiles as ordinal variables in the regression model. ‘Per 1 SD increase’ represents the effect value of postpartum weight retention risk corresponding to each SD increase in body composition.
Model 1: without adjustment.
Model 2: adjusted for early pregnancy BMI, maternal age, ethnicity, household registration type, education level, gravidity, parity, GWG.
Bold values represent statistical significance (P<0.05).
BMI, body mass index; FFM, fat-free mass; FM, fat mass; GWG, gestational weight gain; LM, lean mass; PBF, percentage of body fat.
Table 4. Logistic regression analysis of body composition levels and postpartum weight retention at 42 days postpartum.
| Quartiles of body composition level | ||||||
|---|---|---|---|---|---|---|
| Variables | Quartile 1 | Quartile 2 | Quartile 3 | Quartile 4 | P for trend | Per 1 SD increase |
| PBF, % | <24.20 | 24.20–27.71 | 27.71–31.00 | >31.00 | ||
| N (case/total) | 35/174 | 56/166 | 68/171 | 70/162 | ||
| Model 1 | Ref. | 2.02 (1.24 to 3.32) | 2.62 (1.63 to 4.27) | 3.02 (1.87 to 4.94) | <0.001 | 1.59 (1.35 to 1.89) |
| Model 2 | Ref. | 3.87 (2.17 to 7.05) | 7.58 (4.18 to 14.17) | 16.29 (8.22 to 33.78) | 0.012 | 3.51 (2.70 to 4.62) |
| FM, kg | <13.10 | 13.10–16.27 | 16.27–19.00 | >19.00 | ||
| N (case/total) | 35/173 | 56/167 | 63/165 | 75/168 | ||
| Model 1 | Ref. | 1.99 (1.22 to 3.27) | 2.44 (1.51 to 3.99) | 3.18 (1.98 to 5.18) | <0.001 | 1.60 (1.36 to 1.89) |
| Model 2 | Ref. | 4.64 (2.55 to 8.67) | 9.13 (4.89 to 17.62) | 24.03 (11.67 to 52.35) | 0.005 | 4.15 (3.15 to 5.57) |
| FFM, kg | <38.90 | 38.90–41.65 | 41.65–43.90 | >43.90 | ||
| N (case/total) | 43/169 | 59/175 | 66/166 | 61/162 | ||
| Model 1 | Ref. | 1.49 (0.94 to 2.39) | 1.93 (1.22 to 3.09) | 1.75 (1.10 to 2.81) | <0.001 | 1.24 (1.06 to 1.46) |
| Model 2 | Ref. | 2.00 (1.21 to 3.36) | 3.01 (1.80 to 5.09) | 3.32 (1.94 to 5.78) | 0.334 | 1.56 (1.30 to 1.89) |
| LM, kg | <35.70 | 35.70–38.43 | 38.43–41.00 | >41.00 | ||
| N (case/total) | 41/173 | 51/164 | 75/174 | 62/162 | ||
| Model 1 | Ref. | 1.45 (0.90 to 2.36) | 2.44 (1.54 to 3.89) | 2.00 (1.25 to 3.22) | <0.001 | 1.30 (1.11 to 1.53) |
| Model 2 | Ref. | 2.43 (1.42 to 4.22) | 4.55 (2.67 to 7.92) | 4.67 (2.65 to 8.40) | 0.279 | 1.71 (1.42 to 2.09) |
Data are presented as ORs with corresponding 95% CIs. ‘P for trend’ is the trend effect value obtained by including body composition quartiles as ordinal variables in the regression model. ‘Per 1 SD increase’ represents the effect value of postpartum weight retention risk corresponding to each SD increase in body composition.
Model 1: without adjustment.
Model 2: adjusted for early pregnancy BMI, maternal age, ethnicity, household registration type, education level, gravidity, parity, GWG.
Bold values represent statistical significance (P<0.05).
BMI, body mass index; FFM, fat-free mass; FM, fat mass; GWG, gestational weight gain; LM, lean mass; PBF, percentage of body fat.
The dose–response relationship between body composition levels and the risk of PPWR, analysed using RCS, is illustrated in figure 2 (early pregnancy) and figure 3 (at 42 days postpartum). A negative linear correlation between PBF and FM levels in the first trimester and the risk of PPWR was observed (p-overall <0.001, p-non-linear=0.444–0.501), while ‘J-shaped’ relationships for PBF, FM, FFM and LM levels at 42 days postpartum were identified (p-overall <0.001, p-non-linear=0.306–0.734).
Figure 2. Cubic spline regression of body composition in early pregnancy with postpartum weight retention. (A) PBF, (B) FM, (C) FFM, (D) LM. Adjusted for early pregnancy BMI, maternal age, ethnicity, household registration type, education level, gravidity, parity, gestational weight gain. BMI, body mass index; FFM, fat-free mass; FM, body fat mass; LM, lean mass; PBF, percentage of body fat.
Figure 3. Cubic spline regression of body composition at 42 days postpartum with postpartum weight retention. (A) PBF, (B) FM, (C) FFM, (D) LM. Adjusted for early pregnancy BMI, maternal age, ethnicity, household registration type, education level, gravidity, parity, gestational weight gain. BMI, body mass index; FFM, fat-free mass; FM, fat mass; LM, lean mass; PBF, percentage of body fat.
Discussion
In this retrospective cohort study evaluating the associations of body composition from early pregnancy to 42 days postpartum with the risk of PPWR, we observed that body composition in the first trimester or changes during pregnancy may affect PPWR. The change in weight among the women in this study was 3.55±3.82 kg (7.59±2.23 kg in the PPWR group and 1.46±2.60 kg in the non-PPWR group). PBF and FM during early pregnancy were negatively correlated with PPWR, whereas positive correlations were observed at 42 days postpartum.
Previous studies on the association between prepregnancy weight, gestational weight gain and PPWR were mostly conducted in developed countries.26 Rong et al’s meta-analysis reported that PPWR was positively correlated with gestational weight gain and negatively correlated with prepregnancy BMI,26 which was consistent with our study. However, a recent study from Vietnam showed that, compared with women with normal BMI before pregnancy, underweight women had significantly higher weight retention 1 year postpartum (3.70 kg vs 2.34 kg).27 Similarly, weight retention at 1 year postpartum in the group with excessive weight gain during pregnancy was significantly higher than that in the group with normal weight gain (5.1 kg vs 2.9 kg). In addition, a 7-year follow-up cohort study6 showed that each SD increase in prepregnancy BMI reduced the risk of weight retention at 1 year and 2 years postpartum by 79% and 80%, respectively, while weight gain during pregnancy was not associated with weight retention at 1 year, 2 years, and even 7 years postpartum, which conflicted with our findings. In summary, prepregnancy BMI and gestational weight gain are risk factors for PPWR. Perinatal care should be strengthened to prevent PPWR.
According to previous studies, the association between PPWR and prepregnancy obesity was primarily evaluated using the traditional index-BMI.6 26 28 Although BMI during pregnancy is highly correlated with body fat percentage in overweight women,29 a proportion of women with normal weight may also have abnormal body fat levels. Hence, BMI sometimes cannot accurately assess the nutritional status of pregnant women. Our study found significant differences in PBF, FM and FFM in early pregnancy between the PPWR group and the non-PPWR group. PBF in early pregnancy was lower in the PPWR group (24.00%±4.20% vs 26.06%±4.73%). This negative association was consistent with the results when BMI was used as a predictor.
In addition, PPWR was highly correlated with gestational weight gain, which was mainly associated with maternal fat rather than LM gain.30 Our findings demonstrated significant differences in PBF and FM between the PPWR group and the non-PPWR group. PBF levels were lower during early pregnancy (24.00%±4.20% vs 26.06%±4.73%) and higher at 42 days postpartum (29.08%±4.66% vs 27.00%±4.43%) in the PPWR group. Weight retention in the PPWR group was 7.59 kg, of which 4.85 kg was body fat. Body fat accumulation in the PPWR group was 4.01 kg higher than that in the non-PPWR group (4.85 kg vs 0.87 kg), indicating that almost 64% of PPWR was attributable to the accumulation of body fat during pregnancy. It is well known that FM, especially visceral fat, is associated with insulin resistance, cardiovascular disease and diabetes.31,33 Increased postpartum visceral fat may elevate later risk of metabolic disease, even in women with normal weight.34 Therefore, although postpartum women may lose all the excess weight gained during pregnancy and may regain their prepregnancy weight, the risk of disease due to fat mobilisation may last a lifetime. These mechanisms may have long-term detrimental effects on women’s health. Our findings may help explain why excessive weight gain or fat accumulation during pregnancy is associated with long-term obesity, cardiovascular disease and other metabolic dysfunction risks.
This study used body composition instead of the traditional, widely used BMI to assess the impact of obesity on PPWR with greater precision and accuracy. However, our study also has several limitations: First, this retrospective cohort study is inevitably subject to recall bias. Second, using early pregnancy BMI at the first perinatal visit instead of prepregnancy BMI in multivariate models may not fully reflect prepregnancy conditions, leading to information bias. In addition, owing to untested or unknown parameters, potential confounding bias may remain. For example, a previous study reported that short sleep or postpartum depression was positively associated with weight retention.35 Prenatal lifestyle interventions can effectively improve PPWR.36 Factors such as fibre intake,18 physical activity behaviours,37 breast feeding,38 gestational diabetes mellitus39 and socioeconomic status40 might also be potential confounders for PPWR. Additionally, dietary supplements (such as protein and probiotics)41 42 may be beneficial in reducing muscle loss and improving body composition. However, due to the lack of information on these variables, we did not include them as covariates in the adjusted models. Finally, participants of this study were pregnant women who registered and gave birth in our hospital. Caution should be exercised when extrapolating these findings to other populations.
Conclusions
In summary, our retrospective cohort study showed that PBF and FM in early pregnancy are negatively correlated with PPWR, while positive associations were observed for PBF, FM, FFM and LM at 42 days postpartum. Additionally, changes in body fat contribute the most to PPWR. These findings suggest that managing body composition and its changes can help prevent PPWR.
Acknowledgements
We would like to acknowledge the participants involved for their support and contribution in this study.
Footnotes
Funding: This study was supported by Chengdu Medical Research Foundation (No. 2022653 and No. 2024314), Sichuan Province Maternal and Child Medical Science and Technology Innovation Project (Key project) (No. 22FXZD08) and Scientific Research Project of Sichuan Medical and Health Promotion Association (No. KY2024QN0207). We thank all the participants for their contributions and support to the present study.
Prepublication history for this paper is available online. To view these files, please visit the journal online (https://doi.org/10.1136/bmjopen-2024-092439).
Patient consent for publication: Consent obtained directly from patient(s).
Ethics approval: This study involves human participants. This study was approved by the Ethics Committee of the Chengdu Shuangliu District Maternal and Child Health Care Hospital and was in line with the ethical guidelines of the Declaration of Helsinki of the World Medical Association (No. ky202205). Participants gave informed consent to participate in the study before taking part.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Data availability statement
Data are available upon reasonable request. The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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