Early risk factors and adult person–environment 
relationships in affective disorder

Background. Lower cognitive ability, higher neuroticism and symptoms of anxiety and depression in childhood predict non-psychotic disorder in adulthood. This study examined whether these early risk factors act by modifying relationships with life events close to disease onset in adulthood.Methods. Childhood measures of neuroticism (N) (including maternal N), cognitive ability (CA) and symptoms of anxiety and depression were measured in a national British birth cohort of 5362 individuals born in the week 3–9 March, 1946. At ages 36 and 43 years, mental state examinations were carried out by trained interviewers, and subjects were asked about the occurrence of stressful life events in the previous year (SLE).Results. The effect of aggregated SLEs on mental health was greater in women, in individuals with higher childhood N and poorer childhood mental health. Higher maternal N was also associated with greater sensitivity to SLEs, independent of subject's N, suggesting possible familial transmission of vulnerability. In addition, higher childhood N predicted, independent of later mental health, greater likelihood of reported exposure to SLEs. In general, individuals with higher childhood CA also reported more SLEs.Conclusions. The results suggest that early risk factors for affective disorder exert effects by modifying person–environment relationships close to onset of adult symptoms. Sensitivity to life events may be transmitted from parents to offspring; psychopathological continuity over the life-span may be explained in part by continuity of altered stress sensitivity.

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Ethnic Differences in Adolescent Mental Health Problems: Examining Early Risk Factors and Deviant Peer Affiliation

Journal of Child and Family Studies ◽

10.1007/s10826-017-0792-7 ◽

2017 ◽

Vol 26 (10) ◽

pp. 2889-2899 ◽

Cited By ~ 7

Author(s):

Whitney Mihiroa Gillies ◽

Joseph M. Boden ◽

Myron D. Friesen ◽

Sonja Macfarlane ◽

David M. Fergusson

Keyword(s):

Mental Health ◽

Risk Factors ◽

Ethnic Differences ◽

Mental Health Problems ◽

Adolescent Mental Health ◽

Health Problems ◽

Deviant Peer Affiliation ◽

Peer Affiliation ◽

Early Risk ◽

Early Risk Factors

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The Association Between Growth Trajectories and Mental Health in Early- to Mid-childhood

University of Toronto Journal of Public Health ◽

10.33137/utjph.v1i1.33811 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Alysha A Bartsch ◽

Sarah Carsley ◽

Charles Keown-Stoneman ◽

Jonathon L Maguire ◽

Catherine S Birken

Keyword(s):

Public Health ◽

Mental Health ◽

Risk Factors ◽

Health Status ◽

Internalizing Problems ◽

Externalizing Problems ◽

Mental Health Status ◽

Growth Trajectories ◽

Early Risk ◽

Early Risk Factors

With increasing recognition of mental health’s importance for overall health, public health professionals are seeking to better understand early risk factors for mental illness. A majority of mental health problems emerge during childhood; there is evidence of a particular association between increased childhood growth and poorer mental health. The current study sought to determine the association between growth trajectories during infancy and early childhood (birth to age 5) and mental health (behavioural and emotional difficulties) in early- to mid-childhood (age 3 to 8). The study was conducted among a subset (n=665) of participants from The Applied Research Group for Kids (TARGet Kids!), an ongoing longitudinal cohort study. Five growth trajectories were determined via repeated measures of age- and sex-standardized body mass index (BMI). Mental health was assessed using the Strengths & Difficulties Questionnaire (SDQ) total difficulties, externalizing problems, and internalizing problems scores. The sociodemographic and health characteristics of the sample were described by mental health status (per the SDQ). The sociodemographic and health characteristics of the sample were described by mental health status (per the SDQ). Regression analyses were run to determine the association between growth trajectories and SDQ scores. There was no statistically significant association between increased growth (“rapidly accelerating” trajectory) and SDQ total difficulties (b=1.49[-3.82,6.81],p=0.58), externalizing problems (b=0.31[-3.29,3.91],p=0.86), or internalizing problems (b=1.18[-1.73,4.09],p=0.43). There was a significant association between decelerating growth and increased internalizing problems (b=0.69[0.07,1.31],p=0.03). Current results do not support an association between increased growth and poorer mental health overall in early- to mid-childhood; however, a pattern of decelerating growth may be associated with more internalizing problems. Understanding early risk factors for poor mental health may allow public health researchers to develop targeted interventions and ultimately improve mental health outcomes across the lifespan. Implications and future directions will be discussed.

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The pathway to special education: The role of early risk factors in disability identification

PsycEXTRA Dataset ◽

10.1037/e569872014-001 ◽

2014 ◽

Author(s):

Whitney A. Leboeuf ◽

Benjamin Brumley ◽

John W. Fantuzzo ◽

Cody A. Hostutler

Keyword(s):

Risk Factors ◽

Special Education ◽

Early Risk ◽

Early Risk Factors ◽

Disability Identification

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Sociodemographic and Psychological Risk Factors for Anxiety and Depression: Findings from the Covid-19 Health and Adherence Research in Scotland on Mental Health (CHARIS-MH) Cross-sectional Survey

International Journal of Behavioral Medicine ◽

10.1007/s12529-021-09967-z ◽

2021 ◽

Author(s):

Gill Hubbard ◽

Chantal den Daas ◽

Marie Johnston ◽

Diane Dixon

Keyword(s):

Mental Health ◽

Risk Factors ◽

Social Support ◽

Illness Representations ◽

Gender Effects ◽

Anxiety And Depression ◽

Perceived Threat ◽

Cross Sectional ◽

Psychological Risk Factors ◽

Psychological Risk

Abstract Background Investigations about mental health report prevalence rates with fewer studies investigating psychological and social factors influencing mental health during the Covid-19 pandemic. Study aims: (1) identify sociodemographic groups of the adult population at risk of anxiety and depression and (2) determine if the following social and psychological risk factors for poor mental health moderated these direct sociodemographic effects: loneliness, social support, threat perception, illness representations. Methods Cross-sectional nationally representative telephone survey in Scotland in June 2020. If available, validated instruments were used, for example, Patient Health Questionnaire (PHQ-4) to measure anxiety and depression. Simple linear regressions followed by examination of moderation effect. Results A total of 1006 participants; median age 53 years, 61.4% female, from all levels of area deprivation (i.e., 3.8% in the most deprived decile and 15.6% in the most affluent decile). Analyses show associations of anxiety and depression with sociodemographic (age, gender, deprivation), social (social support, loneliness) and psychological factors (perceived threat and illness representations). Mental health was poorer in younger adults, women and people living in the most deprived areas. Age effects were exacerbated by loneliness and illness representations, gender effects by loneliness and illness representations and deprivation effects by loneliness, social support, illness representations and perceived threat. In each case, the moderating variables amplified the detrimental effects of the sociodemographic factors. Conclusions These findings confirm the results of pre-Covid-19 pandemic studies about associations between sociodemographics and mental health. Loneliness, lack of social support and thoughts about Covid-19 exacerbated these effects and offer pointers for pre-emptive action.

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Early Risk Factors for Obesity in the First 1000 Days—Relationship with Body Fat and BMI at 2 Years

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18158179 ◽

2021 ◽

Vol 18 (15) ◽

pp. 8179

Author(s):

Mercedes Díaz-Rodríguez ◽

Celia Pérez-Muñoz ◽

Jesús Carretero-Bravo ◽

Catalina Ruíz-Ruíz ◽

Manuel Serrano-Santamaría ◽

...

Keyword(s):

Risk Factors ◽

Weight Gain ◽

Body Fat ◽

Early Pregnancy ◽

Body Fat Percentage ◽

Z Score ◽

Fat Percentage ◽

Early Risk ◽

Early Risk Factors ◽

Increased Risk

(1) Background: Obesity is defined as an excessive accumulation of body fat. Several early developmental factors have been identified which are associated with an increased risk of childhood obesity and increased adiposity in childhood. The primary objective of the present study is to analyse the effect of various early risk factors on Body Mass Index (BMI) and body fat percentage at 2 years of age. (2) Methods: A prospective cohort study design was used, with the sample consisting of 109 mother-child pairs from whom data were collected between early pregnancy and 2 years old. Adiposity was determined based on skinfold measurements using the Brooks and Siri formulae. Mean comparison tests (Student’s t-test and ANOVAs) and multiple linear regression models were used to analyse the relationship between early programming factors and dependent variables. (3) Results: Maternal excess weight during early pregnancy (β = 0.203, p = 0.026), gestational smoking (β = 0.192, p = 0.036), and accelerated weight gain in the first 2 years (β = − 0.269, p = 0.004) were significantly associated with high body fat percentage. Pre-pregnancy BMI and accelerated weight gain in the first 2 years were associated with high BMI z-score (β = 0.174, p = 0.047 and β = 0.417, p = 0.000 respectively). The cumulative effect of these variables resulted in high values compared to the baseline zero-factor group, with significant differences in BMI z-score (F = 8.640, p = 0.000) and body fat percentage (F = 5.402, p = 0.002) when three factors were present. (4) Conclusions: The presence of several early risk factors related to obesity in infancy was significantly associated with higher BMI z-score and body fat percentage at 2 years of age. The presence of more than one of these variables was also associated with higher adiposity at 2 years of age. Early prevention strategies should address as many of these factors as possible.

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