Correlations between parental alcohol measures (linear term) at age 4 and 12 years.

<p>Correlations between parental alcohol measures (linear term) at age 4 and 12 years.</p

Factors influencing the probability of birth in urban and rural Bangladesh

This study has been undertaken using data from the 1989 Bangladesh Fertility Survey to determine the significance influences of factors on the probability of birth in the year preceding the survey. The variables selected in this study were grouped into demographic, socio-economic, cultural and decision-making variables. Logistic regression modelling has been used to access the probability of a woman giving birth in urban and rural situations for the selected variables. The study then has emerged some important findings that mother's age, having ever used contraception, child death, women who have ever worked, religion, region of residence, and female independence are the important covariates for explaining the recent fertility in Bangladesh. Results may be useful for policy purposes

Parental alcohol consumption (assessed at age 4 years using linear and binary measures) and childhood conduct problem trajectories.

<p>Parental alcohol consumption (assessed at age 4 years using linear and binary measures) and childhood conduct problem trajectories.</p

Descriptive information for maternal and partner alcohol use for both conduct problems and depressive symptoms.

<p>Descriptive information for maternal and partner alcohol use for both conduct problems and depressive symptoms.</p

A visualization of a cusp catastrophe model.

<p>This figure features two panels: (A) The 3D cusp catastrophe model with stress on the <i>x</i>-axis, connectivity on the <i>y</i>-axis and the state of the system (i.e., <i>D</i>: the total number of active symptoms) on the <i>z</i>-axis; and (B) A 2D visualization of the cusp as depicted in (A). In the case of weak connectivity (top graph in (B)), the system shows smooth continuous behavior in response to increasing stress (green line, invulnerable networks). In the case of strong connectivity (bottom graph in (B)), the system shows discontinuous behavior with sudden jumps from non-depressed to more depressed states and vice versa (red line, vulnerable networks). Additionally, the system with strong connectivity shows two tipping points with in between a so-called forbidden zone (i.e., the dashed part of the red line): in that zone, the state of the system is unstable to such an extent that even a minor perturbation will force the system out of that state into a stable state (i.e., the solid parts of the red line).</p

Parental alcohol use (assessed at age 4 and 12 years using linear alcohol measures) and adolescent depressive symptoms.

<p>Parental alcohol use (assessed at age 4 and 12 years using linear alcohol measures) and adolescent depressive symptoms.</p

An analogy between vulnerability in a network and spacing of domino tiles.

<p>An analogy between vulnerability in a network and spacing of domino tiles.</p

Correlations between parental alcohol measures (linear term) at age 4 and 12 years.

<p>Correlations between parental alcohol measures (linear term) at age 4 and 12 years.</p

The state of the MD system in response to stress for varying connectivity.

<p>The <i>x</i>-axis represents stress while the <i>y</i>-axis depicts the average state of the MD system, <i>D</i>: that is, the total number of active symptoms averaged over every 0.20 range of the stress parameter value. The grey line (and points) depicts the situation where stress is increasing (UP; from -15 to 15, with steps of 0.01) whereas the black line (and points) depicts the situation where stress is decreasing (DOWN; from 15 to -15, with steps of 0.01). The three graphs represent, from left to right, the simulation results for networks with low, medium, and high connectivity, respectively.</p

The inter-individual MD symptom network based on the VATSPUD data.

<p>Each node in the left panel of the figure represents one of the 14 disaggregated symptoms of MD according to DSM-III-R. A line (i.e., edge) between any two nodes represents a logistic regression weight: the line is green when that weight is positive, and red when negative. An edge becomes thicker as the regression weight becomes larger. As an example, the grey circles are the <i>neighbor</i> of the symptom that is encircled in purple (i.e., they have a connection with the purple symptom). The right part of the figure shows the estimated thresholds for each symptom. <i>dep</i>: depressed mood; <i>int</i>: loss of interest; <i>los</i>: weight loss; <i>gai</i>: weight gain; <i>dap</i>: decreased appetite; <i>iap</i>: increased appetite; <i>iso</i>: insomnia; <i>hso</i>: hypersomnia; <i>ret</i>: psychomotor retardation; <i>agi</i>: psychomotor agitation; <i>fat</i>: fatigue; <i>wor</i>: feelings of worthlessness; <i>con</i>: concentration problems; <i>dea</i>: thoughts of death.</p