Prediction of excess pregnancy weight gain using psychological, physical, and social predictors: A validated model in a prospective cohort study

Do Psychological and Behavioural Factors Change Over Pregnancy?

OBJECTIVES

To investigate how psychological and behavioural factors change from the first to the last half of pregnancy.

METHODS

In this prospective cohort study, we assessed the changes in psychological and behavioural factors across 10 domains among 445 women (mean age = 30.9 years) in Ontario, Canada. We collected data using 2 standardized questionnaires administered at <21 and 32-36 weeks of gestation. We computed intraclass correlation coefficients, percentages of no change, decrease, and increase, and mean differences between the 2 surveys.

RESULTS

Most psychological and behavioural factors had intraclass correlation coefficients < 0.50 between the first and the second half of pregnancy, suggesting remarkable changes over the course of pregnancy. We observed significant decreases in self-efficacy, compensatory health beliefs, guilt regarding binge eating, emotional eating, dietary restriction, pregnancy-related nausea and food cravings, sleep duration, and physical activity. We also found increases in anxious and depressive symptoms and the tendency to accept friends' and family's beliefs regarding pregnancy.

CONCLUSIONS

In the first prospective analysis, we found that many psychological and behavioural factors changed significantly over pregnancy.

The association between multidimensional sleep health and gestational weight gain

BACKGROUND

Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep health framework is needed.

OBJECTIVES

This secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n = 745) examined associations between mid-pregnancy sleep health indicators, multidimensional sleep health and gestational weight gain (GWG).

METHODS

Sleep domains (i.e. regularity, nap duration, timing, efficiency and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined 'healthy' sleep in each domain with empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis and composite score defined as the sum of healthy sleep domains. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD) and high (>+1 SD).

RESULTS

Nearly 50% of the participants had a healthy sleep profile (i.e. healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of unhealthy sleep in each domain. The individual sleep domains were associated with a 20%-30% lower risk of low or high GWG. Each additional healthy sleep indicator was associated with a 10% lower risk of low (vs. moderate), but not high, GWG. Participants with late timing, long duration and low efficiency (vs. healthy) profiles had the strongest risk of low GWG (relative risk 1.5, 95% confidence interval 0.9, 2.4). Probabilistic bias analysis suggested that most associations between individual sleep health indicators, sleep health profiles and GWG were biased towards the null.

CONCLUSIONS

Future research should determine whether sleep health is an intervention target for healthy GWG.

Prevalence and related factors of inappropriate gestational weight gain among pregnant women with overweight/ obesity in Thailand

BACKGROUND

An inappropriate gestational weight gain (GWG) among pregnant women with overweight/obesity is a crucial health problem. Its prevalence remains high worldwide, particularly in urban areas. The prevalence and predicting factors in Thailand are lack of evidence. This study aimed to investigate prevalence rates, antenatal care (ANC) service arrangement, predictive factors, and impacts of inappropriate GWG among pregnant women with overweight/obesity in Bangkok and its surrounding metropolitan area.

METHODS

This cross-sectional, retrospective study used four sets of questionnaires investigating 685 pregnant women with overweight/obesity and 51 nurse-midwives (NMs) from July to December 2019 in ten tertiary hospitals. Multinomial logistic regression identified predictive factors with a 95% confidence interval (CI).

RESULT

The prevalence rates of excessive and inadequate GWG were 62.34% and 12.99%. Weight management for pregnant women with overweight/obesity are unavailable in tertiary cares. Over three-fourths of NMs have never received weight management training for this particular group. ANC service factors, i.e., GWG counseling by ANC providers, quality of general ANC service at an excellent and good level, NMs' positive attitudes toward GWG control, significantly decreased the adjusted odds ratio (AOR) of inadequate GWG by 0.03, 0.01, 0.02, 0.20, times, respectively. While maternal factors, sufficient income, and easy access to low-fat foods reduce AOR of inadequate GWG by 0.49, and 0.31 times. In contrast, adequate maternal GWG knowledge statistically increased the AOR of inadequate GWG 1.81 times. Meanwhile, easy access to low-fat foods and internal weight locus of control (WLOC) decreased the AOR of excessive GWG by 0.29 and 0.57 times. Finally, excessive GWG significantly increased the risk of primary C/S, fetal LGA, and macrosomia 1.65, 1.60, and 5.84 times, respectively, while inadequate GWG was not associated with adverse outcomes.

CONCLUSION

Prevalence rates of inappropriate GWG, especially excessive GWG remained high and affected adverse outcomes. The quality of ANC service provision and appropriate GWG counseling from ANC providers are significant health service factors. Thus, NMs should receive gestational weight counseling and management training to improve women's knowledge and practice for gestational weight (GW) control.

Pilot Lifestyle Intervention Effect on Lifestyle Behaviors, Psychosocial Factors, and Affect

Background

This paper presents results of a pilot intervention effect on lifestyle behaviors, psychosocial factors, and affect among overweight or obese pregnant women.

Methods

70 participants were randomized to the intervention or usual care group. During the 20-week intervention, participants completed a weekly online intervention module and joined individual online health coaching. Data were collected at baseline (<17 weeks gestation), 24-27 weeks gestation (T2), and 35-37 weeks gestation (T3). Lifestyle behaviors included dietary intake (caloric, fat, added sugar, fruit, and vegetable) and physical activity (PA). Psychosocial factors were autonomous motivation, self-efficacy, executive functions, and consideration of future consequences (CFC). Affect comprised stress and emotional control. Two-sample t-tests and Cohen's d effect sizes were used to compare between group mean differences in the change from baseline to T2 and T3.

Results

At T2, intervention positively influenced fruit intake (d = 0.47), autonomous motivation for healthy eating (d = 0.36), self-efficacy for healthy eating (d = 0.25) and PA (d = 0.24), executive functions (behavior regulation, d = -0.21; metacognition, d = -0.69), and emotional control (d = 0.79). At T3, the intervention improved PA (d = 0.19), autonomous motivation for healthy eating (d = 0.33), self-efficacy for healthy eating (d = 0.50) and stress management (d = 0.62), executive functions (metacognition, d = -0.46), CFC (d = 0.25), stress (d = -0.45), and emotional control (d = 0.72).

Conclusion

The pilot intervention has positive effects on most psychosocial variables and affect in both the short and long terms.

Development and validation of a screening questionnaire for early identification of pregnant women at risk for excessive gestational weight gain

BACKGROUND

Excessive weight gain during pregnancy is associated with adverse health outcomes for mother and child. Intervention strategies to prevent excessive gestational weight gain (GWG) should consider women's individual risk profile, however, no tool exists for identifying women at risk at an early stage. The aim of the present study was to develop and validate a screening questionnaire based on early risk factors for excessive GWG.

METHODS

The cohort from the German "Gesund leben in der Schwangerschaft"/ "healthy living in pregnancy" (GeliS) trial was used to derive a risk score predicting excessive GWG. Sociodemographics, anthropometrics, smoking behaviour and mental health status were collected before week 12^th of gestation. GWG was calculated using the last and the first weight measured during routine antenatal care. The data were randomly split into development and validation datasets with an 80:20 ratio. Using the development dataset, a multivariate logistic regression model with stepwise backward elimination was performed to identify salient risk factors associated with excessive GWG. The β coefficients of the variables were translated into a score. The risk score was validated by an internal cross-validation and externally with data from the FeLIPO study (GeliS pilot study). The area under the receiver operating characteristic curve (AUC ROC) was used to estimate the predictive power of the score.

RESULTS

1790 women were included in the analysis, of whom 45.6% showed excessive GWG. High pre-pregnancy body mass index, intermediate educational level, being born in a foreign country, primiparity, smoking, and signs of depressive disorder were associated with the risk of excessive GWG and included in the screening questionnaire. The developed score varied from 0-15 and divided the women´s risk for excessive GWG into low (0-5), moderate (6-10) and high (11-15). The cross-validation and the external validation yielded a moderate predictive power with an AUC of 0.709 and 0.738, respectively.

CONCLUSIONS

Our screening questionnaire is a simple and valid tool to identify pregnant women at risk for excessive GWG at an early stage. It could be used in routine care to provide targeted primary prevention measures to women at particular risk to gain excessive gestational weight.

TRIAL REGISTRATION

NCT01958307, ClinicalTrials.gov, retrospectively registered 9 October 2013.

The association between multidimensional sleep health and gestational weight gain: nuMoM2b Sleep Duration and Continuity Study

Background

Although poor sleep health is associated with weight gain and obesity in the non-pregnant population, research on the impact of sleep health on weight change among pregnant people using a multidimensional sleep-health framework is needed. This study examined associations among mid-pregnancy sleep health indicators, multidimensional sleep health, and gestational weight gain (GWG).

Methods

We conducted a secondary data analysis of the Nulliparous Pregnancy Outcome Study: Monitoring Mothers-to-be Sleep Duration and Continuity Study (n=745). Indicators of individual sleep domains (i.e., regularity, nap duration, timing, efficiency, and duration) were assessed via actigraphy between 16 and 21 weeks of gestation. We defined "healthy" sleep in each domain based on empirical thresholds. Multidimensional sleep health was based on sleep profiles derived from latent class analysis. Total GWG, the difference between self-reported pre-pregnancy weight and the last measured weight before delivery, was converted to z-scores using gestational age- and BMI-specific charts. GWG was defined as low (<-1 SD), moderate (-1 or +1 SD), and high (>+1 SD).

Results

Nearly 50% of the participants had a healthy sleep profile (i.e., healthy sleep in most domains), whereas others had a sleep profile defined as having varying degrees of poor health in each domain. While indicators of individual sleep domains were not associated with GWG, multidimensional sleep health was related to low and high GWG. Participants with a sleep profile characterized as having low efficiency, late timing, and long sleep duration (vs. healthy sleep profile) had a higher risk (RR 1.7; 95% CI 1.0, 3.1) of low GWG a lower risk of high GWG (RR 0.5 95% CI 0.2, 1.1) (vs. moderate GWG).

Conclusions

Multidimensional sleep health was more strongly associated with GWG than individual sleep domains. Future research should determine whether sleep health is a valuable intervention target for optimizing GWG.

Synopsis

Study question: What is the association between mid-pregnancy multidimensional sleep health and gestational weight gain?What's already known?: Sleep is associated with weight and weight gain outside of pregnancyWhat does this study add?: We identified patterns of sleep behaviors associated with an increased risk of low gestational weight gain.

Coping with Stress in Complicated Pregnancy and Gestational Weight Gain

Maternal obesity is one of the leading health problems in the world. Excessive gestational weight gain (GWG) can lead to many complications during pregnancy, especially when it is accompanied by diabetes. Moreover, the risk of excessive GWG in pregnant women is significant, irrespective of prenatal counseling. Studies on this subject concerning coping with stress are lacking in the literature. The present work is aimed at evaluating the styles of coping with stress and their relation to GWG in pregnant women with gestational diabetes (GDM) for whom sudden adaptation to dietary management during this period can be challenging. It was indicated that women with GDM reported high stress related to potential maternal-fetal complications and worries about compliance with dietary management. The overall weight gain of participants in pregnancy was determined in connection to their prepregnancy body mass index (BMI) and classified based on the Institute of Medicine guidelines. A standardized psychological scale was used to assess coping styles. The results showed that almost half of the participants did not meet the Institute of Medicine recommendations for weight gain during pregnancy. There were significant correlations between the styles of coping with stress and the GWG. Additionally, low correlations were indicated between emotional, avoidant, task-oriented coping styles and the age of pregnant women with GDM. Regression analysis showed that the stress-coping style that focused on emotions was the most predictive of overall weight gain. There is a need for a better understanding of psychological barriers in achieving the recommended GWG and potential limitations in providers' interventions, particularly for GDM.

A goal set too high: factors associated with planning excess gestational weight gain in a prospective cohort study

OBJECTIVE

This study aimed to understand physical, knowledge, psychological, and lifestyle factors associated with planned excess gestational weight gain (GWG), a strong and potentially modifiable predictor of actual excess GWG, which contributes to maternal and child obesity along with other adverse maternal and fetal outcomes.

METHODS

This is a secondary analysis of data from a prospective cohort study where women completed a questionnaire in early pregnancy. Women were asked to report their planned GWG, which was then categorized as above, within, or below the Institute of Medicine (IOM) guidelines. Univariable and multivariable analyses were performed to identify variables associated with planned excess GWG.

RESULTS

Of 970 women included in the analysis, 300 reported a planned GWG above the IOM guidelines. Predictors of excess planned GWG included reporting healthcare provider recommendations to gain weight above the guidelines (adjusted odds ratio [aOR], 62.17; 95% confidence interval [CI], 13.75-281.03), overestimating first trimester weight gain recommendations (aOR, 1.83; 95% CI, 1.21-2.77), believing in risks to the baby with inadequate GWG (aOR 2.16; 95% CI,1.29-3.60), inaccurate self-perceived prepregnancy body size (aOR, 1.88; 95% CI, 1.22-2.89), low or high emotional suppression (aOR, 1.78; 95% CI, 1.06-2.99; and aOR, 2.57; 95% CI, 1.21-5.45, respectively), physical inactivity (aOR, 1.10; 95% CI, 1.03-1.17), and overweight or obesity (aOR, 5.76; 95% CI, 3.70-8.98; and aOR, 11.46; 95% CI, 6.54-20.06, respectively). Protective factors against planned excess GWG included increased maternal age (aOR, 0.95; 95% CI, 0.92-0.99), and believing in risks to themselves with inadequate GWG (aOR 0.64; 95% CI, 0.42-0.97) or believing in risks to the baby with excess GWG (aOR, 0.49; 95% CI, 0.27-0.88).

CONCLUSIONS

Women with overweight or obesity are at greater risk of prospectively planning excess GWG, and may especially benefit from healthcare provider counseling on appropriate GWG. Other modifiable factors for planned excess GWG included knowledge about risks of inappropriate weight gain and physical inactivity.

Gestational weight gain outside the 2009 Institute of Medicine recommendations: novel psychological and behavioural factors associated with inadequate or excess weight gain in a prospective cohort study

BACKGROUND

Previous studies have noted traditional physical, demographic, and obstetrical predictors of inadequate or excess gestational weight gain, but the roles of psychological and behavioral factors are not well established. Few interventions targeting traditional factors of gestational weight gain have been successful, necessitating exploration of new domains. The objective of this study was to identify novel psychological and behavioral factors, along with physical, demographic, and obstetrical factors, associated with gestational weight gain that is discordant with the 2009 Institute of Medicine guidelines (inadequate or excess gain).

METHODS

We recruited English-speaking women with a live singleton fetus at 8 to 20 weeks of gestation who received antenatal care from 12 obstetrical, family medicine, and midwifery clinics. A questionnaire was used to collect information related to demographic, physical, obstetrical, psychological, and behavioural factors anticipated to be related to weight gain. The association between these factors and total gestational weight gain, classified as inadequate, appropriate, and excess, was examined using stepwise multinomial logistic regression.

RESULTS

Our study population comprised 970 women whose baseline data were obtained at a mean of 14.8 weeks of gestation ±3.4 weeks (standard deviation). Inadequate gestational weight gain was associated with obesity, planned gestational weight gain (below the guidelines or not reported), anxiety, and eating sensibly when with others but overeating when alone, while protective factors were frequent pregnancy-related food cravings and preferring an overweight or obese body size image. Excess gestational weight gain was associated with pre-pregnancy overweight or obese body mass index, planned gestational weight gain (above guidelines), frequent eating in front of a screen, and eating sensibly when with others but overeating when alone, while a protective factor was being underweight pre-pregnancy.

CONCLUSIONS

In addition to commonly studied predictors, this study identified psychological and behavioral factors associated with inadequate or excess gestational weight gain. Factors common to both inadequate and excessive gestational weight gain were also identified, emphasizing the multidimensional nature of the contributors to guideline-discordant weight gain.

Predictors of Gestational Weight Gain Examined As a Continuous Outcome: A Prospective Analysis

Background: Excess gestational weight gain (GWG) is common and adversely affects both mothers and offspring, including increasing the risk of maternal and childhood obesity. GWG is typically examined categorically, with women grouped into categories of those who gain above, within, and below guideline recommendations. Examining GWG as a continuous variable, rather than categorically, allows for a consideration of GWG at a finer level of detail, increasing precision. Methods: We collected exposure data among 970 pregnant women in early gestation using a standardized questionnaire in Ontario, Canada, from 2015 to 2017. Maternal weight and height were extracted from antenatal records. Continuous GWG was calculated using four methods: percentage of ideal weight gain, excess GWG, GWG adequacy ratio, and GWG z-score. We used the stepwise linear regression analyses to select variables associated with GWG. Results: We found that a common set of variables (parity, prepregnancy body mass index, planned pregnancy weight gain, smoking, pregnancy-related food cravings, and fast food intake) significantly predicted GWG in a manner consistent across the four GWG outcomes. Certain psychological factors, including the perception of families' and friends' attitudes toward the food cravings of pregnant women, emotion suppression, compensatory health beliefs coupled with eating unhealthy foods, frequent prepregnancy dietary restraint in carbohydrates, sugar, and meals, preferred prepregnancy body size image, agreeable and conscientious personalities, and depression, also were related with GWG. Conclusions: Our findings demonstrate that psychological factors play an important role in the magnitude of GWG, providing key avenues to inform interventions to support healthy weight gain in pregnancy.

Does Excess First- or Second-Trimester Weight Gain Predict Excess Total Gestational Weight Gain? A Multicentre Prospective Cohort Study

OBJECTIVES

Early excess gestational weight gain (GWG) has been examined as a predictor of total excess GWG in a few international studies; however, Canadian data are lacking. We sought to determine whether early (first- and second-trimester) excess GWG predicted total excess GWG.

METHODS

We conducted an a priori planned secondary analysis of a multicentre prospective study of English-speaking Ontario women with a singleton pregnancy between 8⁰ and 20⁶ weeks gestation. Our primary outcome was prediction of total excess GWG. We calculated the sensitivity, specificity, predictive values, and likelihood ratios, by body mass index (BMI), for excess first- and second-trimester GWG.

RESULTS

Of the 970 women who met the inclusion criteria, 387 and 754, had first- and second-trimester weights recorded in their antenatal record, respectively. For normal, overweight, and obese women, the sensitivity of excess first-trimester GWG for total excess gain was 66%, 68%, and 65%, respectively; and the specificity was 48%, 43%, and 36%, respectively. The sensitivity of excess second-trimester GWG for total excess gain for normal weight, overweight, and obese women was higher, at 92%, 96%, and 95%, respectively; while the specificity was low at 31%, 16%, and 29%, respectively.

CONCLUSION

In the first known Canadian study of early excess weight gain as the predictor of total GWG, we found that excess first-trimester GWG did not predict total excess GWG, but that the sensitivity of excess second-trimester GWG for excess total GWG was high across BMI categories.

Competing priorities: a qualitative study of how women make and enact decisions about weight gain in pregnancy

Background

Despite ample clinical evidence that gaining excess weight in pregnancy results in negative health outcomes for women and infants, more than half of women in Western industrialized nations gain in excess of national guidelines. The influence of socio-demographic factors and weight gain is well-established but not causal; the influence of psychological factors may explain some of this variation.

Methods

This is the qualitative portion of an explanatory sequential mixed-methods study designed to identify predictive psychological factors of excess gestational weight gain (QUAN) and then explain the relevance of those factors (qual). For this portion of the study, we used a qualitative descriptive approach to elicit 39 pregnant women’s perspectives of gestational weight gain, specifically inquiring about factors determined as relevant to excess gestational weight gain by our previous predictive study. Women were interviewed in the latter half of their third trimester. Data were analyzed using a combination of unconstrained deductive content analysis to describe the findings relevant to the predictive factors and a staged inductive content analytic approach to examine the data without a focus on the predictive factors.

Results

Very few participants consistently made deliberate choices relevant to weight gain; most behaviour relevant to weight gain happened with in-the-moment decisions. These in-the-moment decisions were influenced by priorities, hunger, a consideration of the consequence of the decision, and accommodation of pregnancy-related discomfort. They were informed by the foundational information a woman had available to her, including previous experience and interactions with health care providers. The foundational information women used to make these decisions was often incomplete. While women were aware of the guidelines related to gestational weight gain, they consistently mis-applied them due to incorrect understanding of their own BMI. Only one woman was aware that weight gain was linked to maternal and infant health outcomes.

Conclusions

There is an important role for prenatal providers to provide the foundational information to positively influence in-the-moment decisions. Understanding how weight gain guidelines apply to one’s own pre-pregnancy BMI and comprehending the well-established link between gestational weight gain and health outcomes may help women prioritize healthy weight gain amongst many competing factors.