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Differences in Health Care, Family, and Community Factors Associated with Mental, Behavioral, and Developmental Disorders Among Children Aged 2–8 Years in Rural and Urban Areas — United States, 2011–2012

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Abstract

Problem/condition: Mental, behavioral, and developmental disorders (MBDDs) begin in early childhood and often affect lifelong health and well-being. Persons who live in rural areas report more health-related disparities than those in urban areas, including poorer health, more health risk behaviors, and less access to health resources. Reporting period: 2011-2012. Description of system: The National Survey of Children's Health (NSCH) is a cross-sectional, random-digit-dial telephone survey of parents or guardians that collects information on noninstitutionalized children aged <18 years in the United States. Interviews included indicators of health and well-being, health care access, and family and community characteristics. Using data from the 2011-2012 NSCH, this report examines variations in health care, family, and community factors among children aged 2-8 years with and without MBDDs in rural and urban settings. Restricting the data to U.S. children aged 2-8 years with valid responses for child age and sex, each MBDD, and zip code resulted in an analytic sample of 34,535 children; MBDD diagnosis was determined by parent report and was not validated with health care providers or medical records. Results: A higher percentage of all children in small rural and large rural areas compared with all children in urban areas had parents who reported experiencing financial difficulties (i.e., difficulties meeting basic needs such as food and housing). Children in all rural areas more often lacked amenities and lived in a neighborhood in poor condition. However, a lower percentage of children in small rural and isolated areas had parents who reported living in an unsafe neighborhood, and children in isolated areas less often lived in a neighborhood lacking social support, less often lacked a medical home, and less often had a parent with fair or poor mental health. Across rural subtypes, approximately one in six young children had a parent-reported MBDD diagnosis. A higher prevalence was found among children in small rural areas (18.6%) than in urban areas (15.2%). In urban and the majority of rural subtypes, children with an MBDD more often lacked a medical home, had a parent with poor mental health, lived in families with financial difficulties, and lived in a neighborhood lacking physical and social resources than children without an MBDD within each of those community types. Only in urban areas did a higher percentage of children with MBDDs lack health insurance than children without MBDDs. After adjusting for race/ethnicity and poverty among children with MBDDs, those in rural areas more often had a parent with poor mental health and lived in resource-low neighborhoods than those in urban areas. Interpretation: Certain health care, family, and community disparities were more often reported among children with MBDDS than among children without MBDDs in rural and urban areas. Public health action: Collaboration involving health care, family, and community services and systems can be used to address fragmented services and supports for children with MBDDs, regardless of whether they live in urban or rural areas. However, addressing differences in health care, family, and community factors and leveraging community strengths among children who live in rural areas present opportunities to promote health among children in rural communities.
Surveillance Summaries / Vol. 66 / No. 8 March 17, 2017
U.S. Department of Health and Human Services
Centers for Disease Control and Prevention
Morbidity and Mortality Weekly Report
Differences in Health Care, Family, and Community
Factors Associated with Mental, Behavioral, and
Developmental Disorders Among Children
Aged 2–8 Years in Rural and Urban Areas —
United States, 2011–2012
Surveillance Summaries
The MMWR series of publications is published by the Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention (CDC),
U.S. Department of Health and Human Services, Atlanta, GA 30329-4027.
Suggested citation: [Author names; first three, then et al., if more than six.] [Title]. MMWR Surveill Summ 2017;66(No. SS-#):[inclusive page numbers].
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CONTENTS
Introduction ............................................................................................................ 2
Methods .................................................................................................................... 3
Results ....................................................................................................................... 4
Discussion ................................................................................................................8
Limitations ...............................................................................................................9
Future Directions ................................................................................................ 10
Conclusion ............................................................................................................ 10
References ............................................................................................................. 10
Surveillance Summaries
MMWR / March 17, 2017 / Vol. 66 / No. 8 1
US Department of Health and Human Services/Centers for Disease Control and Prevention
Differences in Health Care, Family, and Community Factors Associated
with Mental, Behavioral, and Developmental Disorders Among Children
Aged 2–8 Years in Rural and Urban Areas — United States, 2011–2012
Lara R. Robinson, PhD1
Joseph R. Holbrook, PhD1
Rebecca H. Bitsko, PhD1
Sophie A. Hartwig, MPH1,2
Jennifer W. Kaminski, PhD1
Reem M. Ghandour, DrPH3
Georgina Peacock, MD1
Akilah Heggs, MA1,2
Coleen A. Boyle, PhD4
1Division of Human Development and Disability, National Center on Birth Defects and Developmental Disabilities, CDC, Atlanta, Georgia
2Oak Ridge Institute for Science and Education, CDC Research Participation Programs, Oak Ridge, Tennessee
3Office of Epidemiology and Research, Maternal and Child Health Bureau, Health Resources and Services Administration, Rockville, Maryland
4Office of the Director, National Center on Birth Defects and Developmental Disabilities, CDC, Atlanta, Georgia
Abstract
Problem/Condition: Mental, behavioral, and developmental disorders (MBDDs) begin in early childhood and often affect
lifelong health and well-being. Persons who live in rural areas report more health-related disparities than those in urban areas,
including poorer health, more health risk behaviors, and less access to health resources.
Reporting Period: 2011–2012.
Description of System: The National Survey of Children’s Health (NSCH) is a cross-sectional, random-digit–dial telephone
survey of parents or guardians that collects information on noninstitutionalized children aged <18 years in the United States.
Interviews included indicators of health and well-being, health care access, and family and community characteristics. Using data
from the 2011–2012 NSCH, this report examines variations in health care, family, and community factors among children aged
2–8 years with and without MBDDs in rural and urban settings. Restricting the data to U.S. children aged 2–8 years with valid
responses for child age and sex, each MBDD, and zip code resulted in an analytic sample of 34,535 children; MBDD diagnosis
was determined by parent report and was not validated with health care providers or medical records.
Results: A higher percentage of all children in small rural and large rural areas compared with all children in urban areas had parents
who reported experiencing financial difficulties (i.e., difficulties meeting basic needs such as food and housing). Children in all rural
areas more often lacked amenities and lived in a neighborhood in poor condition. However, a lower percentage of children in small
rural and isolated areas had parents who reported living in an unsafe neighborhood, and children in isolated areas less often lived in
a neighborhood lacking social support, less often lacked a medical home, and less often had a parent with fair or poor mental health.
Across rural subtypes, approximately one in six young children had a parent-reported MBDD diagnosis. A higher prevalence was
found among children in small rural areas (18.6%) than in urban areas (15.2%). In urban and the majority of rural subtypes,
children with an MBDD more often lacked a medical home, had a parent with poor mental health, lived in families with financial
difficulties, and lived in a neighborhood lacking physical and social resources than children without an MBDD within each of
those community types. Only in urban areas did a higher percentage of children with MBDDs lack health insurance than children
without MBDDs. After adjusting for race/ethnicity and poverty among children with MBDDs, those in rural areas more often
had a parent with poor mental health and lived in resource-low neighborhoods than those in urban areas.
Interpretation: Certain health care, family, and community disparities were more often reported among children with MBDDS
than among children without MBDDs in rural and urban areas.
Public Health Action: Collaboration involving health care, family, and community services and systems can be used to address fragmented
services and supports for children with MBDDs, regardless of whether
they live in urban or rural areas. However, addressing differences in
health care, family, and community factors and leveraging community
strengths among children who live in rural areas present opportunities
to promote health among children in rural communities.
Corresponding author: Lara Robinson, National Center on Birth
Defects and Developmental Disabilities, CDC. E-mail: lpr0@cdc.gov;
Telephone: 404-498-3822.
Surveillance Summaries
2 MMWR / March 17, 2017 / Vol. 66 / No. 8 US Department of Health and Human Services/Centers for Disease Control and Prevention
Introduction
Mental health is a critical component of physical health
and development. The onset of mental, behavioral, and
developmental disorders (MBDDs) often occurs in childhood.
Nationally representative data suggest that 15% of U.S.
children aged 2–8 years (i.e., early childhood, as defined by
Healthy People 2020 [HP2020]) (1) have a parent-reported
MBDD diagnosis (2). Treating these conditions early is
important; an HP2020 objective sets a national target for
76% of all children with mental health problems to receive
treatment (1). Factors associated with having a parent-reported
MBDD diagnosis in early childhood include inadequate
insurance coverage, lacking a medical home (patient-centered,
coordinated primary care model), fair or poor parental
mental health, financial difficulties (i.e., “very hard to get by
on your family’s income—hard to cover the basics like food
or housing”), employment difficulties because of child care
issues, living in a neighborhood lacking social support (i.e.,
neighbors who “help each other out,” “watch out for each
other’s children,” and can be “count[ed] on” and “trusted to
help my child”), and living in a neighborhood with limited
amenities (i.e., no sidewalks, parks or playgrounds, recreation
or community centers, or libraries) or in poor condition (i.e.,
with litter or garbage on the street or sidewalk, poorly kept
housing, or vandalism (2). Understanding how these factors
are associated with mental health among young children in
different types of communities might help those who are
developing prevention and intervention programs.
Persons who live in rural communities (compared with those
in urban communities) often have health-related disparities,
including worse health, more health risk behaviors, and less
access to resources (3). Indicators of poor mental health
among adults (e.g., serious mental illness among men, major
depressive episodes among men and women, and recent serious
psychological distress among women) have been found to be
higher in large rural counties than in small rural, suburban, and
urban counties (3). Most studies examining children’s mental
health in rural and urban areas indicate comparable rates of
mental disorders in the two types of areas (4,5). However,
mental disorders might be underreported in rural areas (6).
For example, in an analysis of the Hawaii public health system,
children living in the most rural areas (small rural towns and
isolated rural areas combined) had more substantial mental
health needs than children in suburban areas at the time mental
health treatment was initiated (7).
A 2005 Health Resources and Services Administration
report described availability, accessibility, and acceptability as
a framework to understand the key barriers that affect rural
behavioral health (8); behavioral health includes the services
and programs that prevent, diagnose, and treat symptoms of
mental and neurodevelopmental disorders. The availability and
quality of specialized behavioral health services and providers
often are insufficient to serve children in rural communities
(9). For example, 61.6% of areas with shortages of mental
health professionals are in rural or partially rural areas (10).
Differences in access to behavioral health care might be
reflected in the type of care children receive. A study of
2002–2008 Medical Expenditure Panel Survey data indicated
higher rates of psychopharmacological treatment compared
with counseling services for children aged 5–17 years across
community settings; in addition, compared with children in
urban areas, children in rural areas had significantly higher
rates of any prescriptions for mental disorders (5).
Behavioral health care in rural communities also can
be affected by social acceptability factors such as stigma,
cultural beliefs, and values unique to the rural community
and community subgroups. Stigma and a lack of anonymity
of behavioral health treatment in rural communities can
contribute to delays in seeking care and underuse of care
(6,11). Specifically, black youths in rural areas are half as likely
as white youths in rural areas to use specialized mental health
treatment; overall, among all racial/ethnic groups combined,
parent reports of the effects of MBDDs on the family (i.e.,
economically, socially, and psychologically) and having public
health insurance were positively associated with specialty
mental health use (12).
Accessibility factors, such as lack of knowledge of behavioral
health needs and treatment options, inadequate financing,
limited transportation, and social isolation also can create
behavioral health service barriers for youths in rural areas
(9,11). Among parents of children with special health care needs
(inclusive of MBDDs), those living in rural areas are more likely
to report unmet health care needs caused by transportation and
financial difficulties than those in urban areas (13). Recruiting
and retaining specialized behavioral health providers can be
challenging because of these barriers (9).
A 2015 White House initiative highlighted the need
to strengthen the quality of, access to, and collaboration
within early childhood learning programs, parenting support
programs, health care, and economic support programs to
address rural childhood poverty (14). This initiative also
underscores the complexity of understanding the relationship
between rurality and poverty. Suburban areas have had the
lowest rates of persons who live below the poverty threshold
and many of the most positive health outcomes, whereas the
smallest, most isolated areas with the highest rates of poverty
have reported the poorest health outcomes (3). The negative
effects of childhood poverty on health and development are
well documented (14,15). For example, parent reports of child
Surveillance Summaries
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US Department of Health and Human Services/Centers for Disease Control and Prevention
height and weight from the 2011–2012 National Survey of
Childrens Health (NSCH) indicated that more children aged
10–17 years in rural areas were overweight or obese than those
in urban areas. In addition, both in urban and rural areas, lower
income households were significantly more likely to have an
overweight or obese child than households with higher incomes
within those areas (16). Demographic and family factors (e.g.,
low maternal education, poverty, having public insurance
coverage, and mental health impairment) have accounted
for the increased likelihood of attention-deficit/hyperactivity
disorder (ADHD) among children in rural areas compared
with those in urban areas (5). Although substantial research
indicates that living in neighborhoods with high poverty is
associated with behavioral problems among young children
(15), research that clarifies which specific neighborhood factors
might be associated with mental health among children in rural
communities is lacking.
The collective research suggests that sociodemographic,
health care, and community factors are associated with MBDDs
in children both in rural and urban settings. The prevalence of
childrens MBDDs in rural areas might be confounded by some
of these factors; therefore, examining the variables separately
by area (i.e., urban vs. rural) is important. This report expands
previous analyses of MBDDs and sociodemographic, health
care, family, and community factors among U.S. children aged
2–8 years (2) by examining differences in these factors among
children with and without MBDDs according to whether
they live in in urban, large rural, small rural, or isolated areas.
This report is intended for public health officials, clinicians,
policymakers, and researchers who would like to understand
and address factors associated with MBDDs among children
in rural areas. Findings from this report might help different
types of communities focus their mental health prevention
and intervention efforts for young children while also helping
achieve the HP 2020 objective that 76% of children with
mental health problems receive treatment (1).
Methods
CDC analyzed data from the 2011–2012 NSCH to examine
differences in sociodemographic, health care, family, and
community factors among children aged 2–8 years with and
without MBDDs living in urban, large rural, small rural,
and isolated areas. NSCH is a cross-sectional, random-digit–
dial telephone survey of parents and guardians that collects
information on noninstitutionalized children aged <18 years
in the United States. Interviews included indicators of health
and well-being, health care access, and family and community
characteristics (17) (Table 1). For each identified household
with children, parents and guardians responded to questions
about one randomly selected child in the home. MBDD
diagnosis was determined by parent report and was not
validated with health care providers or medical records. Urban
and rural designations were determined using a census tract–
based classification system and work commuting information.
For the 2011–2012 NSCH, the interview completion rates
(i.e., the percentage of households that completed interviews
among all eligible households that were contacted) were 54.1%
for the landline sample and 41.2% for the cell phone sample.
The overall response rate among all eligible households,
accounting for households that were not successfully contacted,
was 23.0% (17). NSCH attempts to minimize nonresponse bias
by incorporating nonresponse adjustments in the development
of the sampling weights. Among the 50 U.S. states and the
District of Columbia, a total of 847,881 households were
screened for age-eligible children. Within these households,
187,422 reported age-eligible children living or staying in the
household. A total of 95,677 interviews were completed (17).
Sociodemographic variables included the child’s sex, age,
race/ethnicity, 200% of the federal poverty level (FPL)
determined by income and family size (e.g., $44,700 for a
family of four in 2011), highest education of the respondent
or another adult in the household, and primary household
language (English or other). The FPL variable in the NSCH
public use file included data from multiple imputation for the
9.3% of the sample for which household income was missing.
Differences in sociodemographic, health care, family, and
community factors were assessed among children with and
without MBDDs in urban and rural areas.
Restricting the data to U.S. children aged 2–8 years with
valid responses for child age and sex, each MBDD, and zip code
(from which rural-urban commuting areas were determined)
(18) resulted in an analytic sample of 34,535 children. Data
were weighted to account for unequal probability of household
and child selection and for nonresponse. Statistical software was
used to calculate weighted prevalence estimates and prevalence
ratios with 95% confidence intervals (CIs) and to account for
the complex sampling design. Adjusted prevalence ratios with
95% CIs were calculated using weighted logistic regression
models adjusting for poverty (<200% FPL or ≥200% FPL)
and race/ethnicity (non–Hispanic white or other). Estimates
based on small sample sizes were suppressed for confidentiality;
therefore, three variables included in the previous study (2)
were not included here (i.e., child lacks preventive medical
care, parent lacks emotional support, and parent reports
child care problems). Statistical significance was determined
using a ≤0.05 threshold for the p value associated with each
prevalence ratio.
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Results
Sociodemographic factors varied both within and among
residential categories (Table 2). A higher prevalence of children
in rural areas (large rural, small rural, and isolated areas) than
children in urban areas were non-Hispanic white (and were less
often non-Hispanic black or Hispanic), lived in a poor or near-
poor household (i.e., <200% of the FPL), lived in a household
where the highest adult educational level was a high school
education or less, and spoke English as their primary language.
Three health care and family factors differed among rural areas
(large rural, small rural, and isolated areas) (Table 2). A lower
percentage of children in isolated areas than children in urban
areas were reported to lack a medical home and have a parent
with fair or poor mental health; children in large rural and small
rural areas more often lived in families with financial difficulties
TABLE 1. Questions and methods for the National Survey of Children’s Health related to mental, behavioral, and developmental disorders;
rurality; and health care, family, and community factors — United States, 2011–2012
Variable Questions and methods
MBDDs Parent responded yes to at least one question: “Has a doctor or other health care provider ever told you that [child] had [specified
MBDD]?” Specified MBDDs included ADHD, depression, anxiety problems, behavioral or conduct problems such as oppositional
defiant disorder or conduct disorder, Tourette syndrome, autism spectrum disorder, learning disability, intellectual disability,
developmental delay, or speech or other language problems.
Urban or rural residence Urban and rural designations were determined using the four-category classification of the 2006 RUCAs, a census tract–based
classification system.* Urban areas (RUCA codes 1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, and 10.1) include metropolitan areas and
surrounding towns from which commuters flow to an urban area; large rural areas (RUCA codes 4.0, 4.2, 5.0, 5.2, 6.0, and 6.1) include
large towns (micropolitan areas) with populations of 10,000–49,999 and their surrounding areas; small rural areas (RUCA codes 7.0,
7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, and 9.2) include small towns with populations of 2,500–9,999 and their surrounding areas;
isolated areas (RUCA codes 10.0, 10.2, 10.3, 10.4, 10.5, and 10.6) are not near towns with a population of ≥2,500.
Health care
Inadequate insurance Parent responded “no” to at least one of five survey items included in four variables: 1) whether the child has current health insurance
coverage; 2) whether the child had gaps in coverage in the past 12 months; 3) whether the coverage is sufficient to meet the child’s
needs; 4a) whether the family pays out-of-pocket expenses, 4b) and if yes, whether these expenses are usually or always reasonable;
and 5) whether insurance allows the child to see needed health care providers.
No medical home This variable was assessed through 19 survey items coded into five variables and based on the parent reporting the child not having
at least one of the following components of a medical home: having a personal doctor or nurse, having a usual place of care,
receiving family-centered care and care coordination, and for children who need them, getting needed referrals.
Family
At least one parent with fair
or poor mental health
Parent responded “fair” or “poor” (compared with “excellent,“very good,” or “good”) to one of two questions: “In general, what is the
status of [child name]’s [mother’s/your] mental and emotional health?” and “In general, what is the status of [child name]’s [father’s/
your] mental and emotional health?”
Financial difficulties Parent responded “very often” or “somewhat often” (compared with “rarely” or “never”) when asked “Since [the child] was born, how
often has it been very hard to get by on your family’s income, for example, was it hard to cover the basics like food or housing?”
Community
Neighborhood with
limited amenities
Parent responded “no” to at least one of the following statements: “Please tell me if the following places and things are available to
children in your neighborhood, even if [the child] does not actually use them”: 1) sidewalks or walking paths; 2) a park or
playground area; 3) a recreation center, community center, or boys’ or girls’ club; 4) a library or bookmobile.
Neighborhood in poor
condition
Parent responded “yes” to any of the following three questions: “In your neighborhood, is there litter or garbage on the street or
sidewalk? How about poorly kept or rundown housing? How about vandalism such as broken windows or graffiti?”
Neighborhood with little
social support
Parents responded they “definitely agree,” “somewhat agree,“somewhat disagree,” or “definitely disagree” to each of four statements
about their neighborhood or community: “People in this neighborhood help each other out; we watch out for each other’s children
in this neighborhood; there are people I can count on in this neighborhood; if my child were outside playing and got hurt or scared,
there are adults nearby who I trust to help my child.” Responses were scored 1–4 (ranging from “definitely agree” through “definitely
disagree”), and an average score was calculated; averages ≥2.25 indicated a lack of social support.
Neighborhood unsafe Parent reported “never” or “sometimes” (compared with “usually” or “always”) to the question, “How often do you feel [the child] is safe
in your community or neighborhood?”
Abbreviations: ADHD = attention-deficit hyperactivity disorder; MBDD = mental, behavioral, and developmental disorder; RUCA = rural-urban commuting area.
* Source: US Department of Health and Human Services, Health Resources and Services Administration. The health and well-being of children in rural areas: a portrait of
the nation 2011–2012. Rockville, MD: US Department of Health and Human Services; 2015. https://mchb.hrsa.gov/nsch/2011-12/rural-health/pdf/rh_2015_book.pdf
Source: Data Resource Center for Child and Adolescent Health, Child and Adolescent Health Measurement Initiative, Maternal and Child Health Bureau. 2011–2012
National Survey of Children’s Health. Child health indicator and subgroups. SAS codebook, Version 1.0. Baltimore, MD: Child and Adolescent Health Measurement
Initiative; 2013. http://www.childhealthdata.org/docs/nsch-docs/sas-codebook_-2011-2012-nsch-v1_05-10-13.pdf
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US Department of Health and Human Services/Centers for Disease Control and Prevention
than children in urban areas. Several community factors
differed among residential categories. Children in all rural areas
more often lacked amenities such as parks, recreation centers,
sidewalks, and libraries in their neighborhood than children in
urban areas and more often lived in a neighborhood in poor
condition (i.e., with garbage, vandalism, or housing in poor
condition). Children in small rural and isolated areas lived in
an unsafe neighborhood less often than children in urban areas,
and children in isolated areas less often lived in a neighborhood
lacking social support. Prevalence of MBDDs among U.S.
children aged 2–8 years was higher in small rural areas (18.6%)
than in urban areas (15.2%); prevalence of MBDDs in large
rural and isolated areas did not differ from urban areas.
Overall, a higher prevalence of children with an MBDD
experienced health care and family challenges than children
without an MBDD. Within urban areas only, children with
an MBDD more often had inadequate health insurance than
children without an MBDD. Children with an MBDD more
often lacked a medical home in urban areas, small rural areas,
and isolated areas than children without an MBDD. Regardless
of urban or rural status, children with an MBDD more often
than children without had at least one parent with fair or poor
mental health. A higher percentage of parents of children with
an MBDD reported financial difficulties within urban, large
rural, and small rural areas (Figures 1 and 2); data for the
figures are provided (https://stacks.cdc.gov/view/cdc/43792).
In urban, large rural, and small rural areas, children with an
MBDD more often lived in a neighborhood in poor condition
than children without an MBDD. Children with an MBDD in
urban, large rural, and isolated rural areas lacked social support
TABLE 2. Demographic, health care, family, and community factors among children aged 2–8 years in urban, large rural, small rural, and isolated
areas — National Survey of Children’s Health, United States, 2011–2012
Variable
Urban* Large rural* Small rural* Isolated*
% (95% CI)% (95% CI)PR§ (95% CI) % (95% CI)PR§ (95% CI) % (95% CI)PR§ (95% CI)
Overall (row %) 82.4 (81.6–83.1) 9.0 (8.4–9.6) 4.9 (4.5–5.3) 3.7 (3.4–4.1)
Demographic
Race/Ethnicity
White, non-Hispanic 47.4 (46.1–48.7) 62.8 (59.0–66.4) 1.3 (1.2–1.4)66.0 (61.5–70.2) 1.4 (1.3–1.5)71.0 (66.0–75.5) 1.5 (1.4–1.6)
Black, non-Hispanic 14.0 (13.2–15.0) 9.0 (7.2–11.2) 0.6 (0.5–0.8)7.3 (5.7–9.4) 0.5 (0.4–0.7)5.7 (3.7–8.5) 0.4 (0.3–0.6)
Hispanic 27.3 (25.9–28.7) 18.9 (15.4–22.9) 0.7 (0.6–0.8)18.1 (14.1–22.8) 0.7 (0.5–0.8)13.0 (9.3–18.0) 0.5 (0.3–0.7)
Other, non-Hispanic 11.2 (10.4–12.1) 9.4 (7.8–11.3) 0.8 (0.7–1.0) 8.6 (7.0–10.6) 0.8 (0.6–1.0)** 10.4 (8.2–13.1) 0.9 (0.7–1.2)
<200% federal poverty level 43.7 (42.3–45.0) 58.5 (55.2–61.8) 1.3 (1.3–1.4)61.0 (56.4–65.4) 1.4 (1.3–1.5)52.8 (48.0–57.6) 1.2 (1.1–1.3)
No more than high school
education in household
48.7 (47.4–50.1) 57.2 (53.9–60.5) 1.2 (1.1–1.3)55.4 (50.9–59.7) 1.2 (1.1–1.3)56.7 (52.0–61.4) 1.3 (1.1–1.4)
English as primary household
language
80.5 (79.2–81.7) 90.4 (87.0–92.9) 1.1 (1.1–1.2)89.7 (86.0–92.5) 1.1 (1.1–1.2)91.3 (87.7–94.0) 1.1 (1.1–1.2)
Health care
Inadequate insurance 21.5 (20.4–22.6) 20.7 (17.9–23.8) 1.0 (0.8–1.1) 19.7 (16.4–23.5) 0.9 (0.8–1.1) 21.1 (17.5–25.1) 1.0 (0.8–1.2)
No medical home 44.6 (43.2–46.0) 44.3 (40.8–47.8) 1.0 (0.9–1.1) 41.6 (37.5–45.9) 0.9 (0.8–1.0) 36.3 (31.8–41.0) 0.8 (0.7–0.9)
Family
At least one parent with fair
or poor mental health
11.2 (10.2–12.3) 13.6 (11.1–16.7) 1.2 (1.0–1.5) 13.3 (9.8–17.7) 1.2 (0.9–1.6) 8.2 (6.1–10.8) 0.7 (0.5–1.0)**
Financial difficulties 25.1 (23.9–26.3) 30.6 (27.5–34.0) 1.2 (1.1–1.4)29.8 (26.2–33.7) 1.2 (1.0–1.4)** 27.0 (23.1–31.2) 1.1 (0.9–1.3)
Community
Neighborhood with limited
amenities
39.4 (38.0–40.7) 52.8 (49.3–56.4) 1.3 (1.2–1.4)59.8 (55.6–64.0) 1.5 (1.4–1.6)68.6 (63.8–73.0) 1.7 (1.6–1.9)
Neighborhood in poor
condition
27.6 (26.4–28.9) 33.8 (30.4–37.3) 1.2 (1.1–1.4)33.1 (29.5–37.0) 1.2 (1.1–1.4)34.1 (29.8–38.8) 1.2 (1.1–1.4)
Neighborhood with little
social support
20.0 (18.9–21.2) 18.7 (16.0–21.7) 0.9 (0.8–1.1) 18.1 (14.8–22.1) 0.9 (0.7–1.1) 9.1 (7.1–11.5) 0.5 (0.4–0.6)
Neighborhood unsafe 15.3 (14.3–16.4) 13.2 (10.4–16.6) 0.9 (0.7–1.1) 11.6 (9.0–14.7) 0.8 (0.6–1.0)** 6.1 (4.2–8.8) 0.4 (0.3–0.6)
Any MBDD 15.2 (14.3–16.1) 16.6 (14.5–19.0) 1.1 (0.9–1.3) 18.6 (15.6–22.0) 1.2 (1.0–1.5)** 15.8 (12.9–19.1) 1.0 (0.8–1.3)
Abbreviations: CI=confidence interval; MBDD=mental, behavioral, and developmental disorder; PR=prevalence ratio; RUCA = rural-urban commuting area.
* Urban and rural designations were determined using the four-category classification of the 2006 RUCAs, a census tract–based classification system. Urban areas
(RUCA codes 1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, and 10.1) include metropolitan areas and surrounding towns from which commuters flow to an urban area; large
rural areas (RUCA codes 4.0, 4.2, 5.0, 5.2, 6.0, and 6.1) include large towns (micropolitan areas) with populations of 10,000–49,999 and their surrounding areas; small
rural areas (RUCA codes 7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, and 9.2) include small towns with populations of 2,500–9,999 and their surrounding areas; isolated
areas (RUCA codes 10.0, 10.2, 10.3, 10.4, 10.5, and 10.6) are not near towns with a population of ≥2,500 (Source: US Department of Health and Human Services,
Health Resources and Services Administration. The health and well-being of children in rural areas: a portrait of the nation 2011–2012. Rockville, MD: US Department
of Health and Human Services; 2015. https://mchb.hrsa.gov/nsch/2011-12/rural-health/pdf/rh_2015_book.pdf).
Percentages are weighted in the table.
§ Urban is referent group.
Prevalence ratio significant at p<0.01.
** Prevalence ratio significant at p<0.05.
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6 MMWR / March 17, 2017 / Vol. 66 / No. 8 US Department of Health and Human Services/Centers for Disease Control and Prevention
FIGURE 1. Prevalence of selected health care and family factors* among children aged 2–8 years with and without mental, behavioral, and
developmental disorders in urban and rural areas§ — National Survey of Children’s Health, United States, 2011–2012
Urban
Large rural
Small rural
Isolated
0
10
20
30
40
50
60
70
100
Prevalence (%)
With
MBDD Without
MBDD
Inadequate
insurance for
optimal health
No medical
home
At least one parent
with fair or poor
mental health
Financial
diculties
Health care and family factors
Abbreviations: MBDD = mental, behavioral, or developmental disorder; RUCA = rural-urban commuting area.
* Inadequate insurance: Based on a negative response to one of five variables included in the following questions: 1) whether the child has current health insurance
coverage; 2) whether the child had gaps in coverage in the past 12 months, 3) whether the coverage is sufficient to meet the child’s needs; 4a) whether the family
pays out-of-pocket expenses, and if yes, 4b) whether these expenses are usually or always reasonable; and 5) whether insurance allows the child to see needed
health care providers. No medical home: To have a medical home, children must have a personal doctor or nurse, usual source of care, and family-centered care;
children needing referrals or care coordination must also have those criteria met. Parent with fair or poor mental health: Based on responses of “fair” or “poor” (i.e.,
compared with “excellent,“very good,” or “good”) to questions about maternal and paternal mental health. Maternal question: “In general, what is the status of [child
name]’s [mother’s/your] mental and emotional health?” Paternal question: “In general, what is the status of [child name]’s [father’s/your] mental and emotional
health?” Financial difficulties: Based on responses of “very often” or “somewhat often” (compared with “rarely” or “never”) to “Since [the child] was born, how often
has it been very hard to get by on your family’s income, for example, it was hard to cover the basics like food or housing?”
Significant differences in the prevalence of health care and family factors were found between children with and without MBDDs in certain urban and rural areas.
Inadequate insurance: urban areas; no medical home: urban, small rural, and isolated areas; parent with fair or poor mental health: urban, large rural, small rural,
and isolated areas; financial difficulties: urban, large rural, and small rural areas.
§ Urban and rural designations were determined using the four-category classification of the 2006 RUCAs, a census tract–based classification system. Urban areas
(RUCA codes 1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, and 10.1) include metropolitan areas and surrounding towns from which commuters flow to an urban area; large
rural areas (RUCA codes 4.0, 4.2, 5.0, 5.2, 6.0, and 6.1) include large towns (micropolitan areas) with populations of 10,000–49,999 and their surrounding areas; small
rural areas (RUCA codes 7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, and 9.2) include small towns with populations of 2,500–9,999 and their surrounding areas; isolated
areas (RUCA codes 10.0, 10.2, 10.3, 10.4, 10.5, and 10.6) are not near towns with a population of ≥2,500 (Source: US Department of Health and Human Services,
Health Resources and Services Administration. The health and well-being of children in rural areas: a portrait of the nation 2011–2012. Rockville, MD: US Department
of Health and Human Services; 2015. https://mchb.hrsa.gov/nsch/2011-12/rural-health/pdf/rh_2015_book.pdf).
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US Department of Health and Human Services/Centers for Disease Control and Prevention
FIGURE 2. Prevalence of selected community factors* among children aged 2–8 years with and without mental, behavioral, and developmental
disorders in urban and rural areas§ — National Survey of Children’s Health, United States, 2011–2012
Urban
Large rural
Small rural
Isolated
0
10
20
30
40
50
60
70
100
Prevalence (%)
With
MBDD Without
MBDD
Neighborhood
with limited
amenities
Neighborhood in
poor condition
Neighborhood with
little social support
Neighborhood
unsafe
Community factors
Abbreviations: MBDD = mental, behavioral, or developmental disorder; RUCA = rural-urban commuting area.
* Neighborhood with limited amenities: Based on responses of “no” to at least one of the following statements: “Please tell me if the following places and things are
available to children in your neighborhood, even if [the child] does not actually use them”: 1) sidewalks or walking paths; 2) a park or playground area; 3) a recreation
center, community center, or boys’ or girls’ club; 4) a library or bookmobile. Neighborhood in poor condition: Based on responses of “yes” to any of the following
three questions: “In your neighborhood, is there litter or garbage on the street or sidewalk? How about poorly kept or rundown housing? How about vandalism
such as broken windows or graffiti?” Neighborhood with little social support: Based on responses of “definitely agree,” “somewhat agree,“somewhat disagree, or
“definitely disagree” to the following four statements about their neighborhood or community: “People in this neighborhood help each other out; we watch out for
each other’s children in this neighborhood; there are people I can count on in this neighborhood; if my child were outside playing and got hurt or scared, there are
adults nearby who I trust to help my child.” Responses were scored 1–4 (“definitely agree” through “definitely disagree”) and an average score was calculated; averages
≥2.25 indicated a lack of support. Neighborhood unsafe: Based on responses of “never” or “sometimes” (compared with “usually” or “always”) to the question, “How
often do you feel [the child] is safe in your community or neighborhood?”
Significant differences in the prevalence of certain community factors were found between children with and without MBDDs in certain urban and rural areas.
Neighborhood with limited amenities: no areas; neighborhood in poor condition: urban, large rural, and small rural areas; neighborhood with little social support:
urban, large rural, and isolated areas; neighborhood unsafe: no areas.
§ Urban and rural designations were determined using the four-category classification of the 2006 RUCAs, a census tract–based classification system. Urban areas
(RUCA codes 1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, and 10.1) include metropolitan areas and surrounding towns from which commuters flow to an urban area; large
rural areas (RUCA codes 4.0, 4.2, 5.0, 5.2, 6.0, and 6.1) include large towns (micropolitan areas) with populations of 10,000–49,999 and their surrounding areas; small
rural areas (RUCA codes 7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, and 9.2) include small towns with populations of 2,500–9,999 and their surrounding areas; isolated
areas (RUCA codes 10.0, 10.2, 10.3, 10.4, 10.5, and 10.6) are not near towns with a population of ≥2,500 (Source: US Department of Health and Human Services,
Health Resources and Services Administration. The health and well-being of children in rural areas: a portrait of the nation 2011–2012. Rockville, MD: US Department
of Health and Human Services; 2015. https://mchb.hrsa.gov/nsch/2011-12/rural-health/pdf/rh_2015_book.pdf).
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8 MMWR / March 17, 2017 / Vol. 66 / No. 8 US Department of Health and Human Services/Centers for Disease Control and Prevention
in their neighborhood more often than children in those types
of areas who did not have an MBDD (Figures 1 and 2); data for
the figures are provided (https://stacks.cdc.gov/view/cdc/43792).
Among children with an MBDD, a higher prevalence
of those living in any rural area (large, small, and isolated
combined) than those in urban areas had a parent with fair or
poor mental health, lived in families with financial difficulties,
lived in a neighborhood with limited amenities, and lived in
a neighborhood in poor condition. After adjusting for race/
ethnicity and poverty, the only factor that was no longer
associated with rurality was financial difficulties (Table 3).
Discussion
MBDDs are prevalent among young children. The findings
in this report indicate that approximately one in six young
children in rural communities had a diagnosed MBDD. A
higher prevalence was found among children in small rural
areas than among those in urban areas. Children in rural areas
might live in neighborhoods with fewer resources (14) and also
might experience more poverty-related factors and indicators
of family adversity, such as lower parental education and poor
parental mental health (5). Neighborhoods that provide access
to community resources (e.g., playgrounds, libraries, and
community centers) can promote school readiness and social
development among young children (15). Within communities
with few resources, having strong social connections with
family, friends, and the neighborhood can offset some of
the negative effects on parental mental health (e.g., stress
and depression) if those connections involve positive models
(15). In contrast, social isolation, which is common in rural
areas, and poverty can place additional stress on parents,
affecting their mental health and parenting behaviors (19), in
turn affecting the health and development of their children.
Factors such as poor housing conditions and living below
the FPL were associated with increased psychological distress
and allostatic load (a composite measure of physiologic stress
responses) among a sample of school-aged children in rural
New York counties (20). However, parenting behaviors that
create healthy home environments and provide access to
learning experiences in the home (e.g., reading to the child
or having age-appropriate toys) and outside the immediate
community (e.g., going to parks, libraries, or museums outside
the neighborhood) have been shown to mediate child outcomes
in neighborhoods with few resources (15).
These NSCH data and previous research indicate that
children with MBDDs were more negatively affected by certain
health care, family, and community factors than children
without an MBDD (2). In addition, the data in this report
demonstrate similar patterns of these differences across the
rural-urban continuum, suggesting MBDD-related disparities
exist regardless of residency type. However, among families of
TABLE 3. Health care, family, and community factors among children aged 2–8 years with mental, behavioral, and developmental disorders
in urban and rural areas — National Survey of Children’s Health, United States, 2011–2012
Variable
Urban*
Large rural, small
rural, isolated*
Rural-urban
prevalence ratio
Rural-urban adjusted
prevalence ratio
% (95% CI) % (95% CI) (95% CI) (95% CI)
Health care
Inadequate insurance for optimal health 26.9 (24.2–29.8) 24.8 (20.7–29.5) 0.9 (0.8–1.1) 1.0 (0.8–1.2)
No medical home 57.4 (54.2–60.6) 52.4 (47.5–57.4) 0.9 (0.8–1.0) 0.9 (0.9–1.1)
Family
At least one parent with fair or poor
mental health
17.5 (14.9–20.5) 27.6 (22.3–33.6) 1.6 (1.2–2.0)§1.3 (1.0–1.7)
Financial difficulties 33.9 (30.7–37.1) 41.5 (36.6–46.6) 1.2 (1.1–1.4)1.0 (0.9–1.2)
Community
Neighborhood with limited amenities 41.7 (38.5–45.0) 63.0 (57.9–67.7) 1.5 (1.4–1.7)§1.5 (1.3–1.6)§
Neighborhood in poor condition 32.2 (29.1–35.4) 42.4 (37.5–47.5) 1.3 (1.1–1.5)§1.2 (1.0–1.4)
Neighborhood with little social support 24.1 (21.5–27.0) 24.1 (20.1–28.7) 1.0 (0.8–1.2) 1.0 (0.8–1.2)
Neighborhood unsafe 15.7 (13.6–18.0) 13.0 (10.1–16.5) 0.8 (0.6–1.1) 0.9 (0.7–1.2)
Abbreviations: CI=confidence interval; FPL = federal poverty level; RUCA = rural-urban commuting area.
* Urban and rural designations were determined using the four-category classification of the 2006 RUCAs, a census tract–based classification system. Urban areas
(RUCA codes 1.0, 1.1, 2.0, 2.1, 3.0, 4.1, 5.1, 7.1, 8.1, and 10.1) include metropolitan areas and surrounding towns from which commuters flow to an urban area; large
rural areas (RUCA codes 4.0, 4.2, 5.0, 5.2, 6.0, and 6.1) include large towns (micropolitan areas) with populations of 10,000–49,999 and their surrounding areas; small
rural areas (RUCA codes 7.0, 7.2, 7.3, 7.4, 8.0, 8.2, 8.3, 8.4, 9.0, 9.1, and 9.2) include small towns with populations of 2,500–9,999 and their surrounding areas; isolated
areas (RUCA codes 10.0, 10.2, 10.3, 10.4, 10.5, and 10.6) are not near towns with a population of ≥2,500 (Source: US Department of Health and Human Services,
Health Resources and Services Administration. The health and well-being of children in rural areas: a portrait of the nation 2011–2012. Rockville, MD: US Department
of Health and Human Services; 2015. https://mchb.hrsa.gov/nsch/2011-12/rural-health/pdf/rh_2015_book.pdf).
Prevalence ratios adjusted for poverty (<200% FPL or ≥200% FPL) and race/ethnicity (non-Hispanic white or all other races/ethnicities).
§ Prevalence ratio significant at p<0.01.
Prevalence ratio significant at p<0.05.
Surveillance Summaries
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US Department of Health and Human Services/Centers for Disease Control and Prevention
children with MBDDs, rural families had financial difficulties
more often than urban families, and the children also more
often had a parent with poor mental health and lived in
neighborhoods lacking amenities and in poor condition. This
suggests that parents of children in rural areas with MBDDs
report more family and neighborhood adversity than parents
of children in urban areas with MBDDs. Similarly, a previous
study found that rural families caring for a child with special
health care needs arrange and deliver more care in their home,
have higher financial costs for health care, and have more
financial difficulties associated with health care than urban
families caring for a child with special health care needs (13).
Alternate, integrative models of care such as collaborations
between providers of primary health care and behavioral health
care, among school-based services, and between community
and state agencies (e.g., cooperative extension and faith-
based organizations) can improve access to behavioral health
resources for children (6,11). Integrative models of primary
care and behavioral health care can reduce health care costs
and increase quality (6). Strategies that have been identified for
improving access in rural areas also might be effective in urban
areas, including cross-training of primary care and allied health
professionals (9), school-based behavioral health services (11),
and telemedicine (6, 9). School-based behavioral health services
have been associated with reduced stigma and transportation
barriers (11). Although children in racial/ethnic minority groups
might be less likely to use specialized mental health care in
general than white children, in a study of rural North Carolina
counties, school-based behavioral health services were most likely
to be used for treatment and accessed equally among racial/
ethnic groups (12). Telemedicine also holds substantial promise
for improving access to behavioral health care; family-focused
telemedicine and other telemedicine options for children are
now more readily available (14,19). Parenting support programs,
behavioral health care, and integrated community supports can
help address access disparities, promote early intervention, and
mitigate severity within rural communities (6).
Certain findings in this report were unexpected. For
example, compared with young children in urban areas, a
lower percentage of young children in isolated areas lacked
a medical home, and a lower percentage had a parent with
fair or poor mental health. This might suggest that the
previously mentioned community social support mitigated
these factors. Having a medical home improves access to
behavioral health services and improves family functioning
and school participation among children with special health
care needs in rural areas (21). In addition, children in rural
communities, overall and by category, did not have different
levels of insurance coverage than those in urban communities.
Only within urban communities did a higher percentage of
children with MBDDs lack health insurance than children
without MBDDs. Other research indicates that children in
rural areas are more likely than children in urban areas to
have public health insurance (5). This suggests that having a
child with an MBDD might be associated with unique health
care factors for families in urban communities. Collaboration
among health care, family, and community services and systems
can address insufficient access to services (21) and promote
the health and development of young children with MBDDs
both in rural and urban communities (2,9).
Experiences among children in rural areas can vary
substantially, and young children in certain rural communities
might lack family and neighborhood resources more than
children in other rural communities. Isolated rural and small
rural areas also might offer more neighborhood social support
than other rural communities. Focusing on the strengths of the
close relationships among some rural families through family-
focused care is an approach that might help address the mental
health needs both of parents and children (19).
Limitations
The findings in this report are subject to several limitations.
First, relying on parent report of MBDD diagnosis by a health care
provider is subject to recall error and potential social desirability
biases and does not include children with undiagnosed MBDDs.
Research indicates that residents in rural areas might underreport
mental health disorders (6); therefore, the findings might not
represent the association between MBDDs and rural residency.
Second, the data are cross-sectional, and direction of effects or
inferences about causality cannot be made. Third, urban and rural
communities might define and conceptualize neighborhoods in
different ways; therefore, the responses to these questions might
differ in ways not fully measured by the questions administered.
Fourth, the coding variable used to define rurality describes
rurality/urbanicity by population density and work commuting
patterns. These codes are based on 2000 census data and 2004
zip codes; designations of urban areas can change over time.
Fifth, because these are cross-sectional data and represent a single
point in time, they do not reflect changes in residence (e.g., the
possibility that a child moved from an urban area to a rural area
or the converse). Sixth, previous research indicates that rurality
is significantly associated with poverty and other demographic
factors (5); as such, the individual contributions of factors in this
report might be difficult to discern. Finally, these data might be
affected by nonresponse bias even though they have been weighted
to adjust for demographic biases that might have resulted from
the low response rate.
Surveillance Summaries
10 MMWR / March 17, 2017 / Vol. 66 / No. 8 US Department of Health and Human Services/Centers for Disease Control and Prevention
Future Directions
Research examining neighborhood risk and protection for
childhood mental health disorders within rural communities
is sparse. Longitudinal studies of MBDDs, rurality, and
sociodemographic, health care, and community factors
could provide additional data regarding long-term outcomes,
direction of effects, and trends over time. In addition,
examining these health care, family, and community factors
and their associations with specific MBDDs (e.g., ADHD
or speech and language problems) by rural area would allow
for better understanding of barriers and facilitators that
could be used to develop specific approaches to improving
the diagnosis and treatment of these disorders in different
locations. Additional analyses could explore associations
between MBDDs and other health care variables, such as the
receipt of mental health treatment or the number of health care
visits in the past year. In addition, analyses examining specific
disorders could help communities identify specific strengths
and opportunities.
Conclusion
Children in rural communities more often experience
poverty and live in communities that are lacking in amenities
and are in poor condition; these factors have been previously
associated with MBDDs among young children (2,15).
Research also indicates that factors such as access to medical
services, resource-seeking behaviors among parents, and
community social connections might mitigate some of the
negative health and developmental effects of living in higher
poverty neighborhoods (15). MBDDs are prevalent among
young children in various rural and urban communities; many
health care, family, and community disparities were reported
between children with and without MBDDS within rural and
urban categories. Integrative models of behavioral and physical
health care can help promote the health and development of
young children (2) and might address some of the unique
barriers experienced by children living in rural communities
(6,11). Collaboration among and within early learning and
parenting support programs, health care systems, and economic
systems can help promote the health and development of young
children in rural communities by facilitating family access to
behavioral health care and community social and recreational
resources. Addressing rural-urban disparities in neighborhood
resources that allow children to play, read, and socialize also
might present opportunities for prevention and treatment.
Acknowledgments
Benjamin Zablotsky, PhD, Stephen Blumberg, PhD, National Center
for Health Statistics, CDC, Hyattsville, Maryland; Michael H. Fox,
Guest Researcher, National Center on Birth Defects and Developmental
Disabilities, Robin M. Wagner, PhD, Guest Editor, Officeof Public
Health Scientific Services, CDC, Atlanta, Georgia; Oak Ridge Institute
for Science and Education, Oak Ridge, Tennessee; U.S. Department
of Energy, Washington, DC.
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ISSN: 1546-0738 (Print)
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... Unfortunately, many children struggle in their social-emotional development for a variety of reasons and need support to learn and use socialemotional skills . For young children with early social-emotional difficulties, early intervention is imperative to support the development of key competencies and skills (Robinson et al., 2017). ...
... The impact of where children reside is important, as children may be at greater risk for both needing and not having access to social emotional services due to their geographic location. When compared to urban areas, rural children are more likely to exhibit school-based adjustment problems (Rimm-Kaufman et al., 2000) and to be diagnosed with a behavioral or developmental disorder (Robinson et al., 2017). In addition, young children with social-emotional needs who live in rural areas often face additional challenges (e.g., lack of qualified providers, poverty) that also impact development (Morales et al., 2020;Robinson et al., 2017). ...
... When compared to urban areas, rural children are more likely to exhibit school-based adjustment problems (Rimm-Kaufman et al., 2000) and to be diagnosed with a behavioral or developmental disorder (Robinson et al., 2017). In addition, young children with social-emotional needs who live in rural areas often face additional challenges (e.g., lack of qualified providers, poverty) that also impact development (Morales et al., 2020;Robinson et al., 2017). To address these issues, the purpose of this article is to conduct a meta-analysis of social-emotional interventions that have been implemented within rural settings with young children. ...
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For young children with early social-emotional difficulties, early intervention is imperative. A number of interventions are available for young children to promote social-emotional competencies. Yet, little is known regarding the impact of early childhood interventions among rural children. Rural communities have several barriers which impede access to early intervention, and rural children often are at increased risk for social-emotional difficulties. Thus, the purpose of this article is to conduct a meta-analysis of single case design studies of social-emotional interventions that have been implemented within rural settings with young children, in an effort to determine the effects and types of early interventions specific to young children in rural areas. A total of 7 studies with 26 participants and 53 effects comprised the final sample. Findings indicated that all interventions, representing three different component types (i.e., teacher/parent behavior management training, social-emotional competency training, parent involvement/enhancement), produced positive social-emotional outcomes (i.e., improved prosocial behavior and decreased disruptive behavior). Moderating variables (e.g., child characteristics, intervention implementer) that may impact intervention effectiveness were also studied and one variable was significant; specifically, studies published in journals had more impact on outcomes than those which were not published. Implications for future research and policy are provided.
... Finally, a major research gap is how the climate change-mental health or climate change-suicide relationships pertain to sensitive populations and environmental justice and equity. Our paper examines the suicide and climate change relationship among populations stratified by location, age, and sex; however, we are unable to further categorize results by additional demographics, including socioeconomic status, race (Mason et al., 2020;Williams et al., 2016), gender and sexuality (e.g., LGBTQ+) (Newcomb et al., 2020;Sutter & Perrin, 2016), substance misuse (Chorlton & Smith, 2016;Whiting et al., 2020), rurality to a greater extent than incorporated herein (Breslau et al., 2014;Robinson et al., 2017;West et al., 2013), or other descriptors pertaining to protected classes that may be relevant and are often linked to greater incidences of negative mental health outcomes. Additional information, including that produced by quantitative, qualitative, and mixed-methods studies and impact estimates among stratified populations, is needed to describe disproportionate effects of climate change on mental health and vulnerable groups, in particular, in greater detail. ...
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We quantify and monetize changes in suicide incidence across the conterminous United States (U.S.) in response to increasing levels of warming. We develop an integrated health impact assessment model using binned and linear specifications of temperature‐suicide relationship estimates from Mullins and White (2019), in combination with monthly age‐ and sex‐specific baseline suicide incidence rates, projections of six climate models, and population projections at the conterminous U.S. county scale. We evaluate the difference in the annual number of suicides in the U.S. corresponding to 1–6°C of warming compared to 1986–2005 average temperatures (mean U.S. temperatures) and compute 2015 population attributable fractions (PAFs). We use the U.S. Environmental Protection Agency’s Value of a Statistical Life to estimate the economic value of avoiding these mortality impacts. Assuming the 2015 population size, warming of 1–6°C could result in an annual increase of 283–1,660 additional suicide cases, corresponding to a PAF of 0.7%–4.1%. The annual economic value of avoiding these impacts is $2 billion–$3 billion (2015 U.S. dollars, 3% discount rate, and 2015 income level). Estimates based on linear temperature‐suicide relationship specifications are 7% larger than those based on binned temperature specifications. Accounting for displacement decreases estimates by 17%, while accounting for precipitation decreases estimates by 7%. Population growth between 2015 and the future warming degree arrival year increases estimates by 15%–38%. Further research is needed to quantify and monetize other climate‐related mental health outcomes (e.g., anxiety and depression) and to characterize these risks in socially vulnerable populations.
... In addition, family communication can also improve the health-related quality of life among family members [5]. Families have an important role in maintaining health and preventing disease because family members may support each other at all stages of life in ways that other systems cannot [6]. In fact, the economic value of care provided by families over the lifetime of an individual is much greater than that of the health care system [7]. ...
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Background With the release of the Health China Action (2019–2030), family health is receiving increasing attention from experts and scholars. But at present, there is no family health scale in China that involves multidimensional and interdisciplinary commonality. Aim To translate a Short Form of the Family Health Scale (FHS-SF) and to test the reliability and validity of the Chinese version of the FHS-SF. Method A Short Form of the Family Health Scale was Chinese translated with the consent of the original author. A total of 8912 residents were surveyed in 120 cities across China using a multistage sampling method, with gender, ethnicity, and education level as quota variables. Seven hundred fifty participants were selected to participate in this study, and 44 participants were randomly selected to be retested 1 month later. Results The Cronbach’s alpha of the Chinese version of a Short Form the Family Health Scale was 0.83,the Cronbach’s alphas of the four subscales ranged from 0.70 to 0.90, the retest reliability of the scale was 0.75, the standardized factor loadings of the validation factor analysis were above 0.50, GFI = 0.98; NFI = 0.97; RFI = 0.95; RMSEA = 0.07, all within acceptable limits. Conclusion The Chinese version of a Short Form the Family Health Scale has good reliability and validity and can be used to assess the level of family health of Chinese residents.
... Numerous risk factors related to the child, family, and environment have been identified that may contribute to the mental health challenges displayed by young children and often have an "additive" effect such that multiple risk factors lead to increased likelihood of negative outcomes (Gettinger et al., 2010). Approximately one in six young children-ages 2-8 years-in rural areas have mental health challenges, a prevalence rate higher than children in urban areas (Robinson et al., 2017). Additionally, children in the child welfare system have significantly higher rates of mental health disorders as well as trauma exposure (National Child Traumatic Stress Network, 2013). ...
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During the early years of formal education, young students develop a number of formative academic, motor, behavioral, and socioemotional skills that lay the foundation for future learning. Since student mental health in the early grades predicts academic achievement in later grades, mental health interventions are essential at the primary school level. Not only are teachers expected to provide academic instruction, they are now involved in providing students with mental health services, despite a lack of training to do so. The current study sought to gather the perspectives of 38 primary-level educators to gain understanding about mental health knowledge, current approaches to mitigating mental health challenges, and barriers that prevent them from successfully addressing student mental health issues. Using thematic analysis, three themes developed: (1) Educators indicate supporting primary students’ mental health is within their role; (2) Systems-level constraints prevent effective mental health supports; and (3) Staff desire increased mental health resources. Implications for educators and practice are discussed.
... There are numerous strengths of this study including the use of two years of NSCH secondary data that are nationally representative, and the use of measures of built and social environments that have been used in numerous prior studies [40][41][42][43]. There are also limitations that should be noted. ...
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(1) Background: Home tobacco smoke exposure (TSE) and negative neighborhood characteristics adversely affect children’s overall health. The objective was to examine the associations of child TSE status and neighborhood characteristics among U.S. school-aged children. (2) Methods: We conducted a secondary analysis of the 2018–2019 National Survey of Children’s Health (NSCH) data including 17,300 U.S. children ages 6–11 years old. We categorized children’s home TSE status into: (a) no TSE: child did not live with a smoker; (b) thirdhand smoke (THS) exposure alone: child lived with a smoker who did not smoke inside the home; and (c) secondhand smoke (SHS) and THS exposure: child lived with a smoker who smoked inside the home. We conducted a series of weighted linear and logistic regression analyses to assess the associations between child TSE status and neighborhood characteristics, adjusting for covariates. (3) Results: Overall, 13.2% and 1.7% of children were exposed to home THS alone and home SHS and THS, respectively. Compared to children with no TSE, children with home THS exposure alone and children with home SHS and THS exposure had a significantly lower total number of neighborhood amenities and children with SHS and THS exposure had a significantly higher total number of detracting neighborhood elements. (4) Conclusions: Children with TSE demonstrate disparities in the characteristics of the neighborhood in which they live compared to children with no TSE. TSE reduction interventions targeted to children with TSE who live in these neighborhoods are warranted.
Article
Objectives Compare lifetime earning potential (LEP) for developmental and behavioral pediatrics (DBP) to general pediatrics and other pediatric subspecialties. Evaluate association between LEP for DBP and measures of workforce distribution. Methods Using compensation and debt data from 2018-2019 and a net present value analysis, we estimated LEP for DBP compared to general pediatrics and other pediatric subspecialties. We evaluated potential effects of eliminating educational debt, shortening length of fellowship training, and implementing loan repayment programs for pediatric subspecialists. We evaluated the association between LEP for DBP and measures of workforce distribution, including distance to subspecialists, percentage of hospital referral regions (HRRs) with a subspecialist, ratio of subspecialists to regional child population, and fellowship fill rates. Results LEP was lower for DBP than for general private practice pediatrics ($1.9 million less), general academic pediatrics ($1.1 million less), and all other pediatric subspecialties. LEP of DBP could be improved by shortening fellowship training or implementing a loan repayment program. LEP for subspecialists, including DBP, was associated with distance to subspecialists (-0.5 miles/$100,000 increase in LEP, 95%CI -0.98 to -0.08), percentage of HRRs with a subspecialist (+1.1%/$100,000 increase in LEP, 95%CI 0.37 to 1.83), ratio of subspecialists to regional child population (+0.1 subspecialists/100,000 children/$100,000 increase in LEP, 95%CI 0.04 to 0.17), and average 2014-2018 fellowship fill rates (+1% spots filled/$100,000 increase in LEP, 95%CI 0.25 to 1.65). Conclusions DBP has the lowest LEP of all pediatric fields and this is associated with DBP workforce shortages. Interventions to improve LEP may promote workforce growth.
Article
Background Anxiety disorders are among the most common psychiatric disorders in childhood and can develop as early as the preschool years. Therefore, providing young children who display early signs of anxiety with skills to prevent the development of later psychopathology is invaluable. The current study evaluates the effectiveness of Fun FRIENDS, an anxiety prevention and resilience program for young children. Method Fifty-seven kindergartners across three classrooms participated in a 15-week anxiety prevention program and teachers completed a behavioral screening measure and anxiety questionnaire at pre, post, 3 month, and 10-month follow-up assessment points. Results Anxiety positively correlated with emotional symptoms , peer difficulties, and total difficulties at pre-intervention. Anxiety symptoms decreased from pre-intervention to follow-up. Additionally, prosocial behaviors improved and moderated the relationship between pre-and post-intervention anxiety symptoms. Conclusions These findings yield promising implications regarding the effectiveness of prevention and intervention programs on increasing social emotional skills and reducing anxiety symptoms in young children.
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The impact of socioeconomic status (SES) on early child development is well-established, but the mediating role of parental mental health is poorly understood. Data were obtained from The Avon Longitudinal Study of Parents and Children (ALSPAC; n = 13,855), including measures of early SES (age 8 months), key aspects of development during mid-late childhood (ages 7–8 years), and maternal mental health during early childhood (ages 0–3 years). In the first year of life, better maternal mental health was shown to weaken the negative association between SES and child mental health. Better maternal mental health was additionally shown to weaken the association between SES and child cognitive ability. These findings highlight the variability and complexity of the mediating role of parental mental health on child development. They further emphasise the importance of proximal factors in the first year of life, such as parental mental health, in mediating key developmental outcomes.
Chapter
Globalization in the last decades has led to an increase of exchanges through the globe and an expansion of global markets as well as an increase of levels of urbanization through the continents. In particular, urbanization includes environmental, social, and economic changes and factors that may affect the mental health of the general population. In fact, emerging evidence reports higher rates of mental disorders in the urban settings than in rural areas, and social disparities and insecurity may impact on the mental health of the weaker groups of society. Also, the lack of contact with nature in the city and higher levels of pollution are associated with a remarkable rate of psychological distress. Pollution, in particular, is tightly related to the level of industrialization and employment of technology. It has been demonstrated that environmental pollutants (e.g., air pollutants, noise, ionizing radiations, etc.) may impact directly or indirectly on mental health: there may be a direct biological consequence of pollution on the human central nervous system as well as a range of psychological stress generated by the lasting exposure to pollutant agents. This chapter reports emerging evidence regarding the impact of urbanicity and pollution on public mental health and suggests further research and action in order to develop strategies of prevention of mental illness due to the burden of global urbanization.
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Sociodemographic, health care, family, and community attributes have been associated with increased risk for mental, behavioral, and developmental disorders (MBDDs) in children (1,2). For example, poverty has been shown to have adverse effects on cognitive, socio-emotional, and physical development (1). A safe place to play is needed for gross motor development, and accessible health care is needed for preventive and illness health care (3). Positive parenting and quality preschool interventions have been shown to be associated with prosocial skills, better educational outcomes, and fewer health risk behaviors over time (2). Protective factors for MBDDs are often shared (4) and conditions often co-occur; therefore, CDC considered MBDDs together to facilitate the identification of factors that could inform collaborative, multidisciplinary prevention strategies. To identify specific factors associated with MBDDs among U.S. children aged 2-8 years, parent-reported data from the most recent (2011-2012) National Survey of Children's Health (NSCH) were analyzed. Factors associated with having any MBDD included inadequate insurance, lacking a medical home, fair or poor parental mental health, difficulties getting by on the family's income, employment difficulties because of child care issues, living in a neighborhood lacking support, living in a neighborhood lacking amenities (e.g., sidewalks, park, recreation center, and library), and living in a neighborhood in poor condition. In a multivariate analysis, fair or poor parental mental health and lacking a medical home were significantly associated with having an MBDD. There was significant variation in the prevalence of these and the other factors by state, suggesting that programs and policies might use collaborative efforts to focus on specific factors. Addressing identified factors might prevent the onset of MBDDs and improve outcomes among children who have one or more of these disorders.
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While psychology has tended to focus on urban issues in research and practice, rural areas have undergone a series of changes in recent years that have increased the need for behavioral health services. A variety of social and economic factors has contributed both to the increasing needs and to the inability of the existing services to meet them. In this article, the authors survey the literature on rural behavioral health issues, focusing on children and adolescents, to highlight the status of knowledge and approaches to intervention. A conceptual rubric based on the social ecological perspective is used. First, what is known about rural behavioral health and health care for youth is described at the ontogenetic, micro-, meso-, and macrosystem levels. Strategies that have been proposed to address problems in rural behavioral health care are also presented at the different levels. General principles for future intervention and research are proposed that recognize the unique context of rural communities, use local knowledge and ideas, incorporate the efforts of informal systems of care using a strength-based approach, and identify and work toward solving the macrosystem issues that underlie rural health problems. © 2006 Wiley Periodicals, Inc.
Article
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The Caring for Children in the Community Study examined the prevalence of DSM-IV psychiatric disorders and correlates of mental health service use in rural African American and white youth. Four thousand five hundred youth aged 9 to 17 years from 4 North Carolina counties were randomly selected from school databases. Parents completed telephone questionnaires about their children's behavior problems. A second-stage sample of 1302 was identified for recruitment into the interview phase of the study, and 920 (70.7%) of these were successfully interviewed at home using the Child and Adolescent Psychiatric Assessment and related measures of service use. Weighted back to general population estimates, 21.1% of youth had 1 or more DSM-IV psychiatric disorders in the past 3 months. Prevalence was similar in African American (20.5%) and white (21.9%) youth. The only ethnic difference was an excess of depressive disorders in white youth (4.6% vs 1.4%). Thirteen percent of participants (36.0% of those with a diagnosis) received mental health care in the past 3 months. White youth were more likely than African American youth to use specialty mental health services (6.1% vs 3.2%), but services provided by schools showed very little ethnic disparity (8.6% vs 9.2%). The effect of children's symptoms on their parents was the strongest correlate of specialty mental health care. In this rural sample, African American and white youth were equally likely to have psychiatric disorders, but African Americans were less likely to use specialty mental health services. School services provided care to the largest number of youths of both ethnic groups.
Book
Building on the innovative Institute of Medicine reports To Err Is Human and Crossing the Quality Chasm, Quality Through Collaboration: The Future of Rural Health offers a strategy to address the quality challenges in rural communities. Rural America is a vital, diverse component of the American community, representing nearly 20 % of the population of the United States. Rural communities are heterogeneous and differ in population density, remoteness from urban areas, and the cultural norms of the regions of which they are a part. As a result, rural communities range in their demographics and environmental, economic, and social characteristics. These differences influence the magnitude and types of health problems these communities face. Quality Through Collaboration: The Future of Rural Health assesses the quality of health care in rural areas and provides a framework for core set of services and essential infrastructure to deliver those services to rural communities. The book recommends: Adopting an integrated approach to addressing both personal and population health needs Establishing a stronger health care quality improvement support structure to assist rural health systems and professionals Enhancing the human resource capacity of health care professionals in rural communities and expanding the preparedness of rural residents to actively engage in improving their health and health care Assuring that rural health care systems are financially stable Investing in an information and communications technology infrastructure It is critical that existing and new resources be deployed strategically, recognizing the need to improve both the quality of individual-level care and the health of rural communities and populations. © 2005 by the National Academy of Sciences. All rights reserved.
Article
This study uses existing data from Hawaii's public mental health system for children and youth as an example of a state-level examination of service use patterns and health care disparities. The purpose of this study was to compare differences in mental health service utilization between rural and non-rural children, especially use of residential services. This study used a performance measure approach to conduct multi-level modeling on existing administrative data to examine the impact of community factors on service utilization. Rural children were found to have the most serious levels of mental health problems at intake, more likely to be placed in out-of-home care, more likely to receive only out-of-home care, more likely to in stay out-of-home longer, and less likely to receive follow-up care than their non-rural counterparts. Practice, policy, and research implications are discussed.
Article
To examine the barriers and difficulties experienced by rural families of children with special health care needs (CSHCN) in caring for their children. The National Survey of Children with Special Health Care Needs was used to examine rural-urban differences in types of providers used, reasons CSHCN had unmet health care needs, insurance and financial difficulties encountered, and the family burden of providing the child's medical care. We present both unadjusted and adjusted results to allow consideration of the causes of rural-urban differences. Rural CSHCN are less likely to be seen by a pediatrician than urban children. They are more likely to have unmet health care needs due to transportation difficulties or because care was not available in the area; there were minimal other differences in barriers to care. Families of rural CSHCN are more likely to report financial difficulties associated with their children's medical needs and more likely to provide care at home for their children. Examining results from both unadjusted and adjusted odds ratios shows that the burden of care for families of rural CSHCN stems both from socioeconomic differences and health system differences. Policies aimed at achieving equity for rural children will require focusing on both individual factors and the health care infrastructure, including increasing insurance coverage to lessen financial difficulties and addressing the availability of providers in rural areas.
Article
Practitioners in rural areas face particular challenges in providing psychological services, ranging from disparate rates of mental disorders to unique circumstances in treating special populations. In this article, we discuss the burden of mental disorders in rural areas, current trends in integration of mental health care and primary care, and unique concerns practitioners face in treating two special populations in rural areas (children and families, and older adults and their caregivers). Implications for practice are also discussed.
Article
This article provides a comprehensive review of research on the effects of neighborhood residence on child and adolescent well-being. The first section reviews key methodological issues. The following section considers links between neighborhood characteristics and child outcomes and suggests the importance of high socioeconomic status (SES) for achievement and low SES and residential instability for behavioral/emotional outcomes. The third section identifies 3 pathways (institutional resources, relationships, and norms/collective efficacy) through which neighborhoods might influence development, and which represent an extension of models identified by C. Jencks and S. Mayer (1990) and R. J. Sampson (1992). The models provide a theoretical base for studying neighborhood mechanisms and specify different levels (individual, family, school, peer, community) at which processes may operate. Implications for an emerging developmental framework for research on neighborhoods are discussed.
Article
This study merged two theoretical constructs: cumulative risk and allostatic load. Physical (crowding, noise, housing quality) and psychosocial (child separation, turmoil, violence) aspects of the home environment and personal characteristics (poverty, single parenthood, maternal highschool dropout status) were modeled in a cumulative risk heuristic. Elevated cumulative risk was associated with heightened cardiovascular and neuroendocrine parameters, increased deposition of body fat, and a higher summary index of total allostatic load. Previous findings that children who face more cumulative risk have greater psychological distress were replicated among a sample of rural children and shown to generalize to lower perceptions of self-worth. Prior cumulative risk research was further extended through demonstration of self-regulatory behavior problems and elevated learned helplessness.