Additional file 1 of Religiosity and spirituality in the prevention and management of depression and anxiety in young people: a systematic review and meta-analysis

Additional file 1: Appendix 1. Search terms for identifying eligible studies. Appendix 2. Region, age, gender, quality distribution of longitudinal and intervention studies. Appendix 3. Risk of bias. Appendix 4. Gender differences in associations between spirituality and religiosity with depression and anxiety. Appendix 5. Race, ethnicity and faith differences in association of spirituality and religiosity with depression and anxiety. Appendix 6. Spirituality/ Religiosity as a moderator between risk factor and depression/anxiety

Population coverage of prevalence data for common mental disorders: averaged across major depressive disorder, dysthymia and anxiety disorders.

<p>Population coverage of prevalence data for common mental disorders: averaged across major depressive disorder, dysthymia and anxiety disorders.</p

Average population coverage of prevalence data for low prevalence disorders: averaged across schizophrenia, bipolar disorder and eating disorders.

<p>Average population coverage of prevalence data for low prevalence disorders: averaged across schizophrenia, bipolar disorder and eating disorders.</p

Results of systematic reviews conducted to identify community-representative epidemiological data for higher and low prevalence mental disorders.

*<p>Number of data sources by disorder. Note that some studies report data for more than one disorder.</p>**<p>In total 96,349 data sources were identified for the review series (ie. high and low prevalence disorders and disorders with onset in childhood).</p

Estimated global coverage^* of prevalence data for mental disorders by Global Burden of Disease 2010 Study world region.

*<p>Coverage: % of population represented by prevalence studies for mental disorders, adjusted for study age-ranges, gender-coverage and sub-national sampling frames.</p>**<p>GBD World Region: see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065514#pone.0065514.s001" target="_blank">Figure S1</a> for more information on world regions used in the Global Burden of Disease Study 2010.</p

The relationship between the number of days on which young people meet the guidelines and the percentage of young people meeting those guidelines on at least that number of days

<p><b>Copyright information:</b></p><p>Taken from "How should activity guidelines for young people be operationalised?"</p><p>http://www.ijbnpa.org/content/4/1/43</p><p>The International Journal of Behavioral Nutrition and Physical Activity 2007;4():43-43.</p><p>Published online 21 Sep 2007</p><p>PMCID:PMC2045661.</p><p></p> For example, about 30% of young people meet both guidelines on at least 50% of days. Data are shown for MVPA guidelines (top line), screen time guidelines (middle line), and both guidelines (bottom line)

Additional file 1: Table S1. of Does the social context of early alcohol use affect risky drinking in adolescents? Prospective cohort study

Estimates of the prevalence of very risky drinking in the week prior to survey by sex, wave and phase. Table S2. Estimates of incident very risky drinking in late adolescence by wave and sex. Table S3. Estimates of the prevalence of repeated (3+ times) drinking in each context in early adolescence by sex. Table S4. Association between context of drinking in early adolescence and incident very risky drinking in later adolescence. Table S5. Association between joint context of repeated drinking in early adolescence and incident very risky drinking in later adolescence. (DOCX 42 kb

Scatterplots showing the relationship between age and (log-transformed) saliva hormone levels for females and males with hormone values above the detection limit.

To illustrate the longitudinal nature of the data, repeated measures over the follow-up period have been connected (black lines) for 10 randomly selected individuals.</p

Characteristics of university students in Uganda in 2005 (n = 980) and 2010 (n = 1954).

<p>Characteristics of university students in Uganda in 2005 (n = 980) and 2010 (n = 1954).</p

Number (%) of waves with available hormone measurements for each hormone for females and males.

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