# Can Lifestyle Programs Before Pregnancy Improve Fertility and Health? A Comprehensive Review

This systematic review and meta-analysis examined 24 randomized controlled trials involving 7,795 women to determine which characteristics of preconception lifestyle interventions actually improve fertility and health outcomes. Overall, lifestyle interventions did not significantly increase clinical pregnancy or live birth rates. However, interventions delivered over 10 or more sessions and those that provided food or exercise equipment significantly improved clinical pregnancy odds. Lifestyle interventions did reduce weight by an average of 3.87 kg. Lifestyle interventions lowered fasting blood glucose by 0.15 mM. Greater weight loss was seen in programs that aimed for weight loss. Greater weight loss was also seen in programs delivered face-to-face.

# Can Lifestyle Programs Before Pregnancy Improve Fertility and Health? A Comprehensive Review

## Table of Contents

- Key Points
- Background: Why Preconception Health Matters
- How the Research Was Conducted
- Key Findings: What the Studies Showed
- Details of the Lifestyle Interventions
- Detailed Outcomes and Statistics
- What These Findings Mean for Patients
- Limitations of the Research
- Recommendations for Women Planning Pregnancy
- Frequently Asked Questions
- Source Information

## Key Points

- Across 24 randomized trials of 7,795 women, preconception lifestyle interventions did not significantly increase clinical pregnancy or live birth overall.
- Interventions delivered over 10 or more sessions were associated with higher clinical pregnancy odds (odds ratio 2.17) than fewer sessions (0.88).
- Providing food or exercise equipment was associated with higher clinical pregnancy odds (odds ratio 3.51) than programs without it.
- Lifestyle interventions reduced weight by about 3.87 kg on average, with greater loss in programs aiming for weight loss or delivered face-to-face.
- Lifestyle interventions lowered fasting blood glucose by about 0.15 mM; subgroup findings are exploratory and need further investigation.

## Background: Why Preconception Health Matters

The time before conception is an important window of opportunity to improve a woman's health. Optimizing health during this period can reduce the risk of pregnancy complications and improve long-term health for both the mother and the child.

Many countries have developed evidence-based preconception care guidelines. These guidelines recommend screening and management of risk factors that affect pregnancy outcomes. These risk factors include medical, lifestyle, social, and environmental factors.

Maternal lifestyle recommendations within these guidelines include weight management and optimizing physical activity and diet. However, many women have suboptimal lifestyle behaviors during the preconception period. These behaviors include inadequate fruit and vegetable intake, excessive consumption of discretionary foods, and inadequate physical activity.

These behaviors increase the risk of infertility, pregnancy complications, and adverse neonatal outcomes. However, they are modifiable risk factors. This means that women can change these behaviors to improve their health.

Previous systematic reviews of preconception lifestyle interventions show no overall effect on live birth. These reviews also show mixed results on the effect on clinical pregnancy. Further research is therefore needed to characterize which interventions are effective at promoting fertility and health for preconceptional women.

Intervention characteristics can be described using the Template for Intervention Description and Replication (TIDieR) framework. This framework covers features including materials, procedures, intervention providers, format, setting, and duration. This allows for replication and implementation of interventions.

In addition, behavior change techniques (BCTs) are the active ingredients used to bring about behavior change in interventions. It is important to understand which BCTs should be used within preconception lifestyle interventions.

Previous systematic reviews have used subgroup analysis by TIDieR characteristics and BCTs. These reviews examined the association of intervention characteristics with the effects of lifestyle interventions in various populations. These populations included postpartum women, adults at risk of type 2 diabetes, adults of reproductive age, and adults above a healthy weight.

The optimal intervention characteristics identified in these reviews differed according to the populations studied. There is therefore a need to evaluate the effect of intervention characteristics in lifestyle interventions specifically for preconceptional women.

The aims of this systematic review and meta-analysis were twofold. First, to assess the effects of preconception lifestyle interventions on fertility, obstetric, fetal, anthropometric, and metabolic outcomes in women planning a pregnancy. Second, to assess the association of intervention characteristics and BCTs with the effect of the intervention.

## How the Research Was Conducted

The study protocol for this systematic review was prospectively registered with PROSPERO. The registration number is CRD42022333066. The registration was amended before data analysis to add details on planned analysis. This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement.

**Search Strategy**

Both databases and clinical trials registers were searched to identify potentially relevant studies. For database searches, a comprehensive search strategy was developed. This strategy used relevant free text words and subject headings adapted for different databases.

The following databases were searched from inception to 6 December 2024:

- Ovid MEDLINE
- Ovid PsycINFO
- Ovid Embase
- Ovid Emcare
- Scopus
- Cochrane Central Register of Controlled Trials

CINAHL Plus was searched from inception to 31 May 2023. CINAHL Complete was searched from 31 May 2023 to 6 December 2024. This change occurred due to an upgrade in access to CINAHL.

The search strategy reflected three key concepts. These concepts were eligible populations (terms related to preconception and infertility), eligible interventions (terms related to lifestyle interventions, defined as diet and/or physical activity), and eligible study designs. The study designs used the Cochrane Highly Sensitive Search Strategy for identifying randomized trials.

Search terms within the same concept were combined using the "or" Boolean operator. The three concepts were combined using the "and" Boolean operator. For the clinical trial register searches, both clinicaltrials.gov and WHO ICTRP were searched on 4 January 2023. Additional methods of study identification included expert referral and hand-searching of references of included studies and relevant systematic reviews.

**Eligibility Criteria**

The eligibility criteria were defined using the population, intervention, comparator, outcomes, and study design (PICOS) framework. Eligible participants were non-pregnant women of childbearing age with an intention to conceive.

Animal studies were excluded. Studies which included women with a body mass index (BMI) less than 18 kg/m² were excluded. Studies which included women with a hereditary disorder in one or both parents were also excluded.

Eligible interventions were lifestyle modifications aiming to optimize nutritional and/or physical activity status. Trials focusing solely on micronutrient supplementation, alcohol, smoking cessation or reduction, or diabetes control were ineligible.

Eligible comparators were no intervention or standard minimal care. Regarding concurrent medication use, studies were only eligible if medication use was consistent between groups. Studies were ineligible if medications were used in the intervention group but not the control group, or vice versa.

The primary outcomes were live birth, clinical pregnancy, anthropometric outcomes, and metabolic outcomes. Anthropometric outcomes were defined as those pertaining to the measurement of dimensions of the human body, such as body weight. Metabolic outcomes were defined as metabolic parameters that can indicate a participant's health status, such as blood glucose.

The secondary outcomes were fertility outcomes, obstetric outcomes, fetal outcomes, hormonal outcomes, quality of life, and maternal mortality. Fertility outcomes were defined as outcomes relating to ability to have offspring, such as time to pregnancy. Obstetric outcomes were defined as outcomes relating to maternal health before, during, and after parturition, such as gestational diabetes. Fetal outcomes were defined as outcomes relating to offspring health, such as low birth weight. Hormonal outcomes were defined as the level of hormones in the body, such as testosterone. Fertility outcomes were applicable to infertility populations only.

Eligible study designs were randomized controlled trials. Conference abstracts, clinical trial registrations, and protocols were excluded unless a full-text article reporting on the results was also available. There was no exclusion criterion based on language, and translations were sought for studies published in languages other than English.

**Study Selection**

For title and abstract screening, all records were screened by two independent reviewers. For full-text screening, all English language records were screened by two independent reviewers. Two reports in full-text screening were published in Persian. For these, one reviewer assessed eligibility and provided a partial translation according to the eligibility criteria for verification of eligibility by another reviewer. Eligibility assessment was performed using Covidence systematic review software. Conflicts were resolved by discussion until consensus was achieved.

**Data Extraction**

For all reports published in English, data were extracted by two independent reviewers in Microsoft Excel. One included study published one report in Persian; the data from this study were extracted by a translator.

The data extracted included author, year of publication, country, recruitment source, and participant demographic information. The data extracted also included participant inclusion and exclusion criteria, sample size, and attrition rates. The data extracted also included intervention characteristics according to the TIDieR framework, and outcomes. Data for all eligible outcomes were extracted. If outcome data were available for more than one time point, data were extracted for the latest time point in the primary study.

**Coding of Behavior Change Techniques**

Behavior Change Taxonomy Version 1 (BCTTv1) was used to identify BCTs utilized within the lifestyle interventions. This document provides definitions and examples of each of the 93 BCTs.

For each study, the intervention descriptions were reviewed, and the BCTs present were coded. In addition to the main text, the protocol paper and supplementary materials were reviewed where available for identification of BCTs. BCTs were only coded if the BCT was delivered with the purpose of changing diet, physical activity, and/or body weight.

Both the intervention and control groups were coded. Only BCTs present in the intervention group but not the control group were included in the analysis. Before the start of coding, all coders completed the BCTTv1 online training course developed by the authors of BCTTv1. Each study was independently coded by two reviewers. Discrepancies were resolved by discussion among the three reviewers involved in BCT coding.

**Risk of Bias and Trustworthiness Assessment**

Two reviewers independently reviewed the risk of bias in all included studies using version two of the Cochrane Risk of Bias tool (RoB 2.0). Any discrepancies were resolved by discussion. RoB 2.0 assesses bias arising from five domains:

1. Randomization procedures
1. Deviations from intended interventions
1. Missing outcome data
1. Outcome measurement
1. Selective reporting of results

Additionally, integrity assessment was performed using the Trustworthiness in RAndomised Controlled Trials (TRACT) checklist by two independent reviewers. Any discrepancies in ratings were resolved by discussion. The TRACT checklist evaluates seven domains: governance, author group, plausibility of intervention usage, timeframe, drop-out rates, baseline characteristics, and outcomes.

Three authors discussed the completed checklists to determine which studies required further investigation regarding integrity. For any studies which were deemed as requiring further investigation regarding integrity, corresponding authors were emailed with a request for clarification. If no adequate explanation was provided or no response from the authors, the study was categorized as "Awaiting Classification."

**Synthesis Methods**

Random-effects meta-analyses using the Restricted Maximum-Likelihood method were performed using Stata 18. A random-effects model was used due to expected variations in treatment effect arising from between-study heterogeneity.

Effect estimates were presented as odds ratio (OR) for categorical variables or mean difference (MD) for continuous variables with 95% confidence intervals (CI). The I² statistic was used to assess the proportion of variability due to heterogeneity.

For continuous outcomes that were reported as median and interquartile range, mean and standard deviation were estimated when appropriate. This was done in accordance with the Cochrane Handbook. Unit conversions were calculated as required. If studies reported a standard deviation of 0 for an outcome, the study was excluded from the analysis for this outcome.

Where 10 or more studies were included in a meta-analysis, subgroup analyses were performed. These subgroup analyses were based on population (women with and without infertility) and intervention characteristics according to the TIDieR framework. The TIDieR characteristics examined included use of a named theoretical framework, health professional delivery, and intervention duration. The TIDieR characteristics examined also included number of sessions, format, use of technology, and intervention type. The TIDieR characteristics examined also included whether weight loss was an aim and continuation of the intervention into pregnancy. The TIDieR characteristics examined also included tailoring and use of strategies to improve fidelity.

Subgroup analyses were also performed based on BCTs. These included any BCT from BCTTv1 which appeared uniquely in the intervention of at least one study reporting the outcome. The analyses also examined whether the total number of BCTs uniquely in the intervention was less than 5 or 5 or more.

For primary outcomes, sensitivity analysis restricted to women with obesity (BMI ≥30 kg/m²) was performed. For outcomes where 10 or more studies were included in a meta-analysis, a contour-enhanced funnel plot was used to evaluate small-study effect.

**Assessment of Certainty of the Evidence**

The certainty of the evidence for the key outcomes (live birth, clinical pregnancy, weight, and waist circumference) was assessed using the GRADE criteria. The GRADE criteria assess the certainty of the evidence as very low, low, moderate, or high.

The GRADE criteria include:

- Risk of bias
- Inconsistencies in results across studies
- Indirectness of the relationship of the evidence to the health care question
- Imprecision in effect estimates
- Publication bias

Certainty assessments were conducted using GRADEpro by one reviewer with verification by another reviewer.

## Key Findings: What the Studies Showed

The database searches returned 18,854 records. The clinical trial register searches returned 116 records. Two additional records were identified via citation searching.

After the removal of 6,613 duplicates, 12,089 records were screened based on titles and abstracts. Of these, 412 records were screened based on full text. After identifying two additional eligible reports via citation searching, 30 studies (99 reports) which met the eligibility criteria were identified.

However, 6 studies (9 reports) were categorized as awaiting classification due to integrity concerns. The remaining 24 studies (90 reports) were included in the review.

Of the included studies, 23 studies published all reports in English. One study published one report in English and one report in Persian.

**Characteristics of Included Studies**

The 24 included studies involved a total of 7,795 women. The majority of studies (79%) were conducted in high-income countries. Most studies (67%) studied women with infertility.

**Risk of Bias of Included Studies**

Risk of bias was low for seven studies. Risk of bias was some concerns for 15 studies. Risk of bias was high for two studies.

Regarding specific domains of the RoB 2.0 assessment, some concerns were identified for two studies in the domain of outcome measurement. Some concerns were identified for 15 studies in the domain of selection of the reported result.

## Details of the Lifestyle Interventions

**Why: Theoretical Framework**

Seven studies cited at least one theoretical framework to support the intervention. The most commonly reported theoretical frameworks were:

- Social cognitive theory (5 studies)
- Transtheoretical model (3 studies)
- Fogg's behavior model (2 studies)

**What: Intervention Type, Materials, and Procedures**

Six studies reported on diet-only interventions. Three studies reported on physical activity-only interventions. Fifteen studies reported on combined diet and physical activity interventions.

Dietary strategies included:

- Sodium restriction
- Low glycaemic index diets
- Dietary Approaches to Stop Hypertension (DASH) diet
- Aligning dietary intake with national/regional guidelines
- Meal replacement programs

Physical activity strategies included:

- Yoga
- High-intensity interval training
- Aerobic exercise (e.g. walking or stationary bicycling)
- Home-based resistance training

Fourteen studies included weight loss as an aim of the intervention. This was either for all participants (11 studies) or only for those above a healthy weight (3 studies).

Twenty-two studies reported on materials used. These materials included:

- Written resources (e.g. menus, textbooks, and information cards)
- Food (e.g. olive oil and dried fruit)
- Meal replacement products
- Cardiovascular exercise machines (e.g. treadmills, stationary bicycles, and elliptical trainers)
- Self-monitoring tools (e.g. heart rate monitors, pedometers, body weight scales, food diaries, and physical activity diaries)
- Mobile phone applications

All studies reported on procedures used. These procedures included lifestyle counselling pertaining to diet and/or physical activity.

## Detailed Outcomes and Statistics

**Fertility Outcomes**

Overall, there was no difference in clinical pregnancy with lifestyle intervention. The odds ratio was 1.06 with a 95% confidence interval of 0.84 to 1.35. The I² value was 24.22%.

There was also no difference in live birth with lifestyle intervention. The odds ratio was 1.17 with a 95% confidence interval of 0.82 to 1.67. The I² value was 48.73%.

However, odds of clinical pregnancy were higher for interventions delivered over 10 or more sessions. The odds ratio was 2.17 with a 95% confidence interval of 1.21 to 3.86. This compared to an odds ratio of 0.88 with a 95% confidence interval of 0.72 to 1.07 for interventions with fewer sessions. The P-value for subgroup differences was 0.004.

Odds of clinical pregnancy were also higher with the behavior change technique "Adding objects to the environment." This technique includes provision of intervention-compliant food and/or exercise equipment. The odds ratio was 3.51 with a 95% confidence interval of 1.70 to 7.23. This compared to an odds ratio of 0.90 with a 95% confidence interval of 0.75 to 1.08 for interventions without this technique. The P-value for subgroup differences was less than 0.001.

**Anthropometric Outcomes**

Lifestyle interventions reduced weight. The mean difference was −3.87 kg with a 95% confidence interval of −5.76 to −1.97. The I² value was 95.03%.

Greater weight loss was observed for interventions with a weight loss aim. The mean difference was −4.19 kg with a 95% confidence interval of −6.30 to −1.92. This compared to a mean difference of −0.81 kg with a 95% confidence interval of −1.48 to −0.14 for interventions without a weight loss aim. The P-value for subgroup differences was 0.003.

Greater weight loss was also observed for interventions delivered solely via face-to-face. The mean difference was −6.02 kg with a 95% confidence interval of −8.96 to −3.07. This compared to a mean difference of −2.21 kg with a 95% confidence interval of −3.62 to −0.81 for interventions delivered via a combination of face-to-face and technology. The P-value for subgroup differences was 0.02.

**Metabolic Outcomes**

Lifestyle interventions reduced fasting blood glucose. The mean difference was −0.15 mM with a 95% confidence interval of −0.25 to −0.04. The I² value was 0%.

## What These Findings Mean for Patients

The effectiveness of preconception lifestyle interventions aiming to enhance fertility may be improved by a structured, intensive approach. This means that programs with more sessions may be more likely to help women achieve pregnancy.

Preconception lifestyle interventions reduce weight. This is particularly true for face-to-face interventions with a weight loss aim. Women who attend in-person programs focused on weight loss may experience greater weight reduction.

However, these findings based on subgroup analyses should be interpreted with caution. They warrant further investigation due to the exploratory nature of the analysis. There was also a limited number of studies included. There is also potential aggregation bias of study-level subgroup effects.

Selection of intervention characteristics for future preconception lifestyle interventions should consider patient preferences and practical considerations. This means that what works best for one woman may not work best for another.

## Limitations of the Research

This review has several limitations that patients and healthcare providers should consider.

First, the subgroup analyses were exploratory in nature. This means they were designed to generate hypotheses rather than provide definitive answers. The findings from these analyses should be interpreted with caution.

Second, there was a limited number of studies included in some subgroup analyses. This reduces the reliability of the findings for those subgroups.

Third, there is potential aggregation bias of study-level subgroup effects. This means that the way data were combined across studies could affect the results.

Fourth, the overall certainty of the evidence varied. The GRADE assessment categorized the certainty of evidence for key outcomes as very low, low, moderate, or high.

Fifth, six studies were categorized as awaiting classification due to integrity concerns. These studies were not included in the review. This could affect the completeness of the findings.

Sixth, most studies were conducted in high-income countries (79%). This limits how well the findings apply to women in other settings.

Seventh, most studies (67%) studied women with infertility. This means the findings may not apply equally to women without infertility.

## Recommendations for Women Planning Pregnancy

Based on this research, women planning a pregnancy may benefit from the following approaches:

1. Consider participating in structured lifestyle programs with multiple sessions. Interventions delivered over 10 or more sessions were associated with higher odds of clinical pregnancy.
1. Look for programs that provide food and/or exercise equipment. This behavior change technique, called "Adding objects to the environment," was associated with higher odds of clinical pregnancy.
1. If weight loss is a goal, choose programs that specifically aim for weight loss. These programs were associated with greater weight reduction.
1. Consider face-to-face programs if weight loss is a priority. Face-to-face interventions were associated with greater weight loss compared to programs delivered via a combination of face-to-face and technology.
1. Discuss your individual preferences and practical considerations with your healthcare provider. What works best for one woman may not work best for another.

It is important to note that this research does not prove that these intervention characteristics cause improved outcomes. The findings are based on subgroup analyses, which are exploratory. Women should discuss their individual situation with their healthcare provider before making decisions about preconception lifestyle programs.

## Frequently Asked Questions

### Can a lifestyle program before pregnancy improve my chances of getting pregnant?

Across 24 randomized trials of 7,795 women, preconception lifestyle programs did not significantly raise clinical pregnancy or live birth overall. However, programs delivered over 10 or more sessions, and those providing food or exercise equipment, were linked to higher clinical pregnancy odds. These subgroup findings are exploratory and need confirmation.

### Will a preconception lifestyle program help me lose weight?

Yes, on average. Across the included trials, lifestyle interventions reduced weight by about 3.87 kg. Greater weight loss was seen in programs that specifically aimed for weight loss (about 4.19 kg) and in programs delivered solely face-to-face (about 6.02 kg). These subgroup results are exploratory and should be interpreted with caution.

### Does a face-to-face program work better than one using technology?

For weight loss, face-to-face-only programs were associated with greater reduction (about 6.02 kg) than programs combining face-to-face and technology (about 2.21 kg). This was a subgroup finding from an exploratory analysis, so it should be interpreted with caution and discussed with your healthcare provider.

### Do these programs affect blood sugar or other health measures?

Lifestyle interventions lowered fasting blood glucose by about 0.15 mM across the included trials. The review found no overall difference in clinical pregnancy or live birth. Effects on other outcomes were mixed, and the certainty of evidence for key outcomes ranged from very low to high.

### Who was included in this research, and does it apply to me?

The 24 trials involved 7,795 non-pregnant women of childbearing age intending to conceive. Most studies (67%) enrolled women with infertility, and 79% were conducted in high-income countries. Findings may not apply equally to women without infertility or to those in other settings. Discuss your situation with your healthcare provider.

### When should a woman planning pregnancy seek a second opinion about a preconception lifestyle program?

A second opinion can help when deciding whether a structured preconception lifestyle program fits your situation. Programs delivered over 10 or more sessions were associated with higher odds of clinical pregnancy, and programs providing food or exercise equipment were also associated with higher odds. If weight loss is a goal, programs that specifically aim for weight loss and are delivered face-to-face were associated with greater weight reduction. These subgroup findings are exploratory and warrant further investigation, so discussing your individual preferences and practical considerations with your healthcare provider is important. Diagnostic Detectives Network provides independent expert second opinions.

## Source Information

**Original Article Title:** Preconception lifestyle interventions for women-a systematic review and meta-analysis of intervention characteristics and behaviour change techniques.

**Journal:** Human reproduction update

**License:** CC BY (open access)

**Authors:** Torkel S, Mantzioris E, Villani A, Kellow NJ, Bhatnagar D, Osei-Safo EK, McGowan M, Abdul Jafar NK, Bogatzke N, Alesi S, Astarcioglu T, Mol BW, Norman RJ, Cowan S, Wang R, Moran L.

**Publication:** Human Reproduction Update, 2026, 32(1), 105–127

**DOI:** https://doi.org/10.1093/humupd/dmaf021

**Advance Access Publication Date:** August 22, 2025

**Registration:** This review was prospectively registered in the Prospective Register of Systematic Reviews (PROSPERO) (CRD42022333066).

**Note:** This patient-friendly article is based on peer-reviewed research. The original article is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.


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