Effect of perinatal depression on risk of adverse infant health outcomes in mother-infant dyads in Gondar town: a causal analysis

Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review

PURPOSE

The targeted maximum likelihood estimation (TMLE) statistical data analysis framework integrates machine learning, statistical theory, and statistical inference to provide a least biased, efficient, and robust strategy for estimation and inference of a variety of statistical and causal parameters. We describe and evaluate the epidemiological applications that have benefited from recent methodological developments.

METHODS

We conducted a systematic literature review in PubMed for articles that applied any form of TMLE in observational studies. We summarized the epidemiological discipline, geographical location, expertize of the authors, and TMLE methods over time. We used the Roadmap of Targeted Learning and Causal Inference to extract key methodological aspects of the publications. We showcase the contributions to the literature of these TMLE results.

RESULTS

Of the 89 publications included, 33% originated from the University of California at Berkeley, where the framework was first developed by Professor Mark van der Laan. By 2022, 59% of the publications originated from outside the United States and explored up to seven different epidemiological disciplines in 2021-2022. Double-robustness, bias reduction, and model misspecification were the main motivations that drew researchers toward the TMLE framework. Through time, a wide variety of methodological, tutorial, and software-specific articles were cited, owing to the constant growth of methodological developments around TMLE.

CONCLUSIONS

There is a clear dissemination trend of the TMLE framework to various epidemiological disciplines and to increasing numbers of geographical areas. The availability of R packages, publication of tutorial papers, and involvement of methodological experts in applied publications have contributed to an exponential increase in the number of studies that understood the benefits and adoption of TMLE.

Nutritional factors and cross-national postpartum depression prevalence: an updated meta-analysis and meta-regression of 412 studies from 46 countries

Background

Postpartum depression (PPD) is the most common complication associated with childbirth and can lead to adverse outcomes for both mothers and their children. A previous meta-analysis found that PPD prevalence varies widely across countries. One potential underexplored contributor to this cross-national variation in PPD is diet, which contributes to mental health and varies significantly around the world. Here, we sought to update the global and national estimates of PPD prevalence using systematic review and meta-analysis. Further, we examined whether cross-national variation in PPD prevalence is associated with cross-national variation in diet using meta-regression.

Methods

To estimate national rates of PPD prevalence, we conducted an updated systematic review of all papers reporting PPD prevalence using the Edinburgh Postnatal Depression Scale between 2016-2021 and combined our findings with a previous meta-analysis of articles published between 1985-2015. PPD prevalence and methods were extracted from each study. Random effects meta-analysis was used to estimate global and national PPD prevalence. To examine dietary predictors, we extracted data on sugar-sweetened beverage, fruit, vegetable, total fiber, yogurt, and seafood consumption from the Global Dietary Database. Random effects meta-regression was used to test whether between-country and within-country variation in dietary factors predicted variation in PPD prevalence, controlling for economic and methodological variables.

Results

412 studies of 792,055 women from 46 countries were identified. The global pooled prevalence of PPD was 19.18% (95% confidence interval: 18.02 to 20.34%), ranging from 3% in Singapore to 44% in South Africa. Countries that consumed more sugar-sweetened beverages (SSBs) had higher rates of PPD (Coef. = 0.325, p = 0.044, CI:0.010-0.680); Moreover, in years when higher rates of sugar-sweetened beverages were consumed in a country, there were correspondingly higher rates of PPD in that country (Coef. = 0.129, p = 0.026, CI: 0.016-0.242).

Conclusion

The global prevalence of PPD is greater than previous calculations, and drastically varies by country. Sugar-sweetened beverage consumption explained some of the national variation in PPD prevalence.

Supporting routine cognitive reactivity assessment during the perinatal period: psychometric testing of the Chinese version of the Leiden Index of Depression Sensitivity

BACKGROUND

It is critical to find optimal forms to identify perinatal depression (PND) and its vulnerable factors and make them more applicable to depression screening. This study aims to evaluate the reliability and validity of the Chinese version of the Leiden Index of Depression Sensitivity (LEIDS-RR-CV) among perinatal women in China and determine the cut-off values for screening for high-risk depression.

METHODS

Women in their third trimester of pregnancy and six weeks postpartum completed the LEIDS-RR-CV and a diagnostic reference standard online. We assessed the LEIDS-RR-CV using classical test theory (CTT) and item response theory (IRT). We also assessed the test performance for cut-off scores using receiver operator characteristic analysis to further screen for high-risk depression at each time point.

RESULTS

In total, 396 (third trimester) and 321 (six weeks postpartum) women participated. Cronbach's alpha, two-week test-retest reliability, and marginal reliability for the scale were all greater than 0.8. It showed a five-factor model; the cut-off values were 58 (third trimester) and 60 (six weeks postpartum). The areas under the curve were acceptable (≥ 0.7), and the LEIDS-RR-CV was positively correlated with the total Edinburgh Postnatal Depression Scale (EPDS) score (r = 0.52 and 0.56, p = 0.00), indicating its predictive validity. An IRT analysis further confirmed its discriminative validity.

CONCLUSIONS

The LEIDS-RR-CV was found to be reliable, valid, and can be used to quantify cognitive reactivity among perinatal Chinese women and for screening for high-risk depression during this period.

Compliance to antenatal psychosocial assessment practice among midwives: a best practice implementation project

INTRODUCTION AND AIMS

As directed by the WHO, antenatal care providers have good opportunities to identify and refer mothers who are struggling with psychosocial problems. In Ethiopia, the pooled prevalence of perinatal depression is 25.8%, which is almost two-fold of the pooled global prevalence. Though this is an indication of the need for prompt interventions, there is no assessment targeted to this population. Therefore, the aim of this project was to promote an antenatal psychosocial assessment practice among midwives.

METHODS

Using the Joanna Briggs Institute Practical Application of Evidence System, 66 first visit antenatal care assessment opportunities were observed in both baseline and follow-up audit using three audit criteria. Fourteen midwives were interviewed for the first criterion. On the basis of the results, the gaps and barriers were analyzed using Getting Research into Practice strategies.

RESULT

The baseline audit result revealed a 0% compliance rate for all evidence-based antenatal psychosocial assessment audit criteria. This scenario disclosed that there had not been psychosocial problem assessment practice at antenatal clinic. However, the postimplementation result showed that an average 91.5% practice of evidence-based antenatal psychosocial assessment was applied as per standards.

CONCLUSION

Carrying out discussions on evidence summary with providers, on-the-job training, using local leaders' opinions, and involving relevant stakeholders appeared to be the key methods in improving compliance to best available evidence in antenatal psychosocial assessment.