The extent to which structural gender inequality contributes to macro-level differences in postpartum depression (PPD) remains largely unknown.

To examine the association of structural gender inequalities with national-level prevalence estimates of PPD symptoms.

Meta-analytically derived national-level estimates for the prevalence of PPD symptoms – based on the Edinburgh Postnatal Depression Scale (EPDS) – were combined with economic (e.g., income inequality), health (e.g., infant mortality rate), sociodemographic (e.g., urban population), and structural gender inequality variables (e.g., abortion policies) for 40 countries (276 primary studies). Data came from a prior meta-analysis on PPD prevalence and international agencies (e.g., UNICEF). Meta-regression techniques and traditional p-value based stepwise procedures, complemented with a Bayesian model averaging approach, were used for a robust selection of variables associated with national-level PPD symptom prevalence. Sensitivity analyses excluded primary studies with small sample sizes or countries lacking evidence for psychometric properties of the EPDS.

Income inequality (β = 0.04, 95% CI = 0.02 to 0.07) and abortion policies (β = 0.02, 95% CI = 0.00 to 0.03) were the only variables included in the final, adjusted model, accounting for 60.7% of the variance in PPD symptoms across countries. Gradual liberalizations of abortion policies were associated with a 2% decrease in national-level PPD symptom prevalence. Results were robust to sensitivity analyses.

Structural gender inequalities might be social determinants of PPD, as the liberalization of abortion policies seem to impact women’s perinatal mental health on a population level. More research on structural gender inequality is needed to guide policy and practice.

No significant relationships.

Videoconferencing in psychiatry allows psychiatric counseling to be dealt remotely. A number of human randomised clinical trials (RCTs) on this topic were conducted but not systematically analysed since 2005.

A meta-analysis was undertaken to test the hypothesis of non-inferiority of remote psychiatric counseling, including both assessment and treatment, compared to face-to-face setting. Focus of research was the general psychiatric approach, which includes pharmacotherapy, counseling and some not specific psychotherapeutic techniques such as listening, reformulation and clarification among others. Specific forms of psychotherapies were not included in this analysis.

RCTs including ≥ 10 subjects per arm were identified in Medline, the Cochrane Library, Embase and the reference list of single papers. A random-effect and a mixed-effect model served for test the hypothesis under analysis.

Twenty-six RCTs were included in the analysis, involving 765 (assessment) and 1585 patients (efficacy). The non-inferiority of remote psychiatric counseling was reported both for assessment and treatment. Heterogeneity could not be excluded for assessment, but was excluded for treatment while taking into account clinical and study related variables (P-values = 0.003 and 0.06, respectively).

High levels of consistency between remote and in vivo psychiatric assessment is reported. Efficacy of remote psychiatric counseling was shown to be not inferior compared to in vivo settings. Heterogeneity could not be excluded for assessment, and further analyses are mandatory. The presence of multiple diagnoses included in the analysis was a limit of the present investigation.

The purpose of this paper is to describe variation, over the months of the year, in major depressive episode (MDE) prevalence. This is an important aspect of the epidemiological description of MDE, and one that has received surprisingly little attention in the literature. Evidence of seasonal variation in MDE prevalence has been weak and contradictory. Most studies have sought to estimate the prevalence of seasonal affective disorder using cut-points applied to scales assessing mood seasonality rather than MDE. This approach does not align with modern classification in which seasonal depression is a diagnostic subtype of major depression rather than a distinct category. Also, some studies may have lacked power to detect seasonal differences. We addressed these limitations by examining the month-specific occurrence of conventionally defined MDE and by pooling data from large epidemiological surveys to enhance precision in the analysis.

Data from two national survey programmes (the National Population Health Survey and the Canadian Community Health Survey) were used, providing ten datasets collected between 1996 and 2013, together including over 500,000. These studies assessed MDE using a short form version of the Composite International Diagnostic Interview (CIDI) for major depression, with one exception being a 2012 survey that used a non-abbreviated version of the CIDI. The proportion of episodes occurring in each month was evaluated using items from the diagnostic modules and statistical methods addressing complex design features of these trials. Overall month-specific pooled estimates and associated confidence intervals were estimated using random effects meta-analysis and a gradient was assessed using a meta-regression model that included a quadratic term.

There was considerable sampling variability when the month-specific proportions were estimated from individual survey datasets. However, across the various datasets, there was sufficient homogeneity to justify the pooling of these estimated proportions, producing large gains in precision. Seasonal variation was clearly evident in the pooled data. The highest proportion of episodes occurred in December, January and February and the lowest proportions occurred in June, July and August. The proportion of respondents reporting MDE in January was 70% higher than August, suggesting an association with implications for health policy. The pattern persisted with stratification for age group, sex and latitude.

Seasonal effects in MDE may have been obscured by small sample sizes in prior studies. In Canada, MDE has clear seasonal variation, yet this is not addressed in the planning of services. These results suggest that availability of depression treatment should be higher in the winter than the summer months.

To combine evidence from randomized controlled trials to assess the effect of Fe-fortified foods on mean Hb concentration in children (<10 years).

We conducted a meta-analysis of randomized, controlled, Fe-fortified feeding trials that evaluated Hb concentration. The weighted mean difference was calculated for net changes in Hb by using random-effects models. Meta-regression and covariate analyses were performed to explore the influence of confounders on the net pooled effect.

Trials were identified through a systematic search of PubMed, the Cochrane Library and secondary references.

Eighteen studies covering 5142 participants were identified. The duration of feeding of fortified foods ranged from 6 to 12 months in these studies.

Eighteen studies were included and evaluated in the meta-analysis. The overall pooled estimate of Hb concentration showed a significant increase in the fortification group compared with the control group (weighted mean difference = 5·09 g/l; 95 % CI 3·23, 6·95 g/l; I2 = 90 %, τ2 = 18·37, P < 0·0001). Meta-regression analysis indicated that duration of feeding was positively related to the effect size (regression coefficient = 0·368; 95 % CI 0·005, 0·731; P < 0·05). The net pooled effect size after removing the confounders was 4·74 (95 % CI 3·08, 6·40) g/l.

We observed an association between intake of Fe-fortified foods and Hb concentration in children aged <10 years. Fe-fortified foods could be an effective strategy for reducing Fe-deficiency anaemia in children.

Summarizing the epidemiology of major depressive disorder (MDD) at a global level is complicated by significant heterogeneity in the data. The aim of this study is to present a global summary of the prevalence and incidence of MDD, accounting for sources of bias, and dealing with heterogeneity. Findings are informing MDD burden quantification in the Global Burden of Disease (GBD) 2010 Study.

A systematic review of prevalence and incidence of MDD was undertaken. Electronic databases Medline, PsycINFO and EMBASE were searched. Community-representative studies adhering to suitable diagnostic nomenclature were included. A meta-regression was conducted to explore sources of heterogeneity in prevalence and guide the stratification of data in a meta-analysis.

The literature search identified 116 prevalence and four incidence studies. Prevalence period, sex, year of study, depression subtype, survey instrument, age and region were significant determinants of prevalence, explaining 57.7% of the variability between studies. The global point prevalence of MDD, adjusting for methodological differences, was 4.7% (4.4–5.0%). The pooled annual incidence was 3.0% (2.4–3.8%), clearly at odds with the pooled prevalence estimates and the previously reported average duration of 30 weeks for an episode of MDD.

Our findings provide a comprehensive and up-to-date profile of the prevalence of MDD globally. Region and study methodology influenced the prevalence of MDD. This needs to be considered in the GBD 2010 study and in investigations into the ecological determinants of MDD. Good-quality estimates from low-/middle-income countries were sparse. More accurate data on incidence are also required.

Abnormal levels of biomarkers in cerebrospinal fluid (CSF) and atrophy of medial temporal lobe (MTL) structures on magnetic resonance imaging (MRI) are being used increasingly to diagnose early Alzheimer's disease (AD). We evaluated the claim that these biomarkers can detect preclinical AD before behavioural (i.e. memory) symptoms arise.

We included all relevant longitudinal studies of CSF and MRI biomarkers published between January 2003 and November 2008. Subjects were not demented at baseline but some declined to mild cognitive impairment (MCI) or to AD during follow-up. Measures of tau and beta-amyloid in CSF, MTL atrophy on MRI, and performance on delayed memory tasks were extracted from the papers or obtained from the investigators.

Twenty-one MRI studies and 14 CSF studies were retrieved. The effect sizes of total tau (t-tau), phosphorylated tau (p-tau) and amyloid beta 42 (aβ42) ranged from 0.91 to 1.11. The effect size of MTL atrophy was 0.75. Memory performance had an effect size of 1.06. MTL atrophy and memory impairment tended to increase when assessed closer to the moment of diagnosis, whereas effect sizes of CSF biomarkers tended to increase when assessed longer before the diagnosis.

Memory impairment is a more accurate predictor of early AD than atrophy of MTL on MRI, whereas CSF abnormalities and memory impairment are about equally predictive. Consequently, the CSF and MRI biomarkers are not very sensitive to preclinical AD. CSF markers remain promising, but studies with long follow-up periods in elderly subjects who are normal at baseline are needed to evaluate this promise.