Does a Medical Home Influence the Effect of Low Birthweighton Health Outcomes?

Joanne Salas • Pamela K. Xaverius •

Jen Jen Chang

Published online: 25 March 2012

� Springer Science+Business Media, LLC 2012

Abstract The objective of this study was to investigate

the possible modifying effect of medical home on the

association between low birthweight and children’s health

outcomes. The analytic sample included children 5 years

and under from the 2007 National Survey of Children’s

Health whose mothers were the primary respondents and

who had non-missing covariate information (n = 19,356).

Controlling for sociodemographic factors, logistic and ordi-

nal regression models estimated the presence of develop-

mental, mental/behavioral or physical health outcomes,

condition severity, and health status by birthweight, medical

home, and their interaction. Prevalence estimates of physical,

developmental, mental/behavioral and severe conditions

among those with any conditions as well as fair/poor overall

health were 8.9, 6.8, 2.4, 41.6, and 2.5 %, respectively.

Overall, low compared to normal birthweight children had a

higher prevalence of physical and developmental conditions

and fair/poor health (15.2 vs. 8.3 %, 11.1 vs. 6.4 %, 4.5 vs.

2.3 %, respectively). Medical home did not significantly

modify the effect of birthweight on health outcomes; how-

ever, prevalence of all outcomes was higher for children

without a medical home. Adjusted models indicated that low

birthweight children were almost twice as likely as normal

birthweight children to have a physical or developmental

condition and poorer overall health, regardless of having a

medical home. Having a medical home was associated with

equally improved health outcomes among normal and low

birthweight children. Adequacy and frequency of medical

home care should be investigated further, especially among

low birthweight children.

Keywords Low birthweight � Medical home �Child development � Child health � National Survey

of Children’s Health

Introduction

The decades-long rise and/or stagnation in United States

low birthweight (LBW) and preterm (PTB) birth rates have

put more infants than ever at increased risk of disability [1, 2].

It is estimated that approximately 8.1 % of infants are born

LBW [3], with 67 % of LBW babies born preterm [4],

costing the United States approximately $26 billion annually

in medical and educational expenses [3]. When babies are

both LBW and PTB, they are at greatest risk of neonatal

death or a lifetime of challenges [5].

There is extant literature describing that very LBW

(1,000–1,499 g) children, compared to normal birthweight

(NBW), are more at risk of psychosocial (e.g. attention deficit

hyperactivity disorder, depression, anxiety, poor adaptive

functioning), medical (e.g. asthma, vision and hearing prob-

lems, epilepsy), and learning/cognitive impairments [2, 5–10].

Moderately LBW infants (1,500–2,499 g) are also at an

increased risk for health, learning, and behavioral problems

[11]. Along the continuum of infants born at varying degrees

of LBW, all have been shown to be at an increased risk for

behavioral and psychosocial difficulties later in life [12–16].

There is a small, growing body of literature suggesting that

additional care, monitoring, and intervention can help families

J. Salas (&) � P. K. Xaverius

Department of Family and Community Medicine, School

of Medicine, Saint Louis University, 1402 S. Grand Blvd.,

O’Donnell Hall, 2nd Floor, Saint Louis, MO 63104, USA

e-mail: salasj@slu.edu

J. J. Chang

Department of Community Health, School of Public Health,

Saint Louis University, Saint Louis, MO 63104, USA

123

Matern Child Health J (2012) 16:S143–S150

DOI 10.1007/s10995-012-1003-1

manage LBW infants, much like the medical home model of

care [17]. In fact, the national recommendation is that all

children have a medical home, defined by the American

Academy of Pediatrics (AAP) as care that is accessible,

continuous, comprehensive, family-centered, coordinated,

compassionate, and culturally effective [18, 19]. This family-

centered model of care is related to improved child behavior

and functioning [20, 21] and can provide more effective,

timelier care [22]. Efficacy studies, focusing on children with

special healthcare needs (CSHCN), are limited, but have

shown improved health outcomes (including mental health),

lower healthcare costs, and greater general health ratings [22–

25], making it a valuable care delivery model for high risk

children. Other studies found that comprehensive care lead to

fewer life-threatening illnesses and PICU admissions among

high-risk infants as well as fewer hospitalizations among

children with asthma [26, 27], suggesting that a medical home

may provide necessary secondary and tertiary prevention for

improved functioning and outcomes.

Proper preventative, continuous care from providers,

such as that offered through medical homes, has been

shown to optimize health outcomes, mostly for CSHCN but

also non-CSHCN [22–25]. However, only about 13 % of

CSHCN are LBW compared to 10 % of non-CSHCN [24],

making it difficult to interpret previous efficacy findings for

LBW children. Also, previous findings suggest that chronic

care management is improved among higher risk children,

but evidence is lacking on whether the benefit of a medical

home is greater among LBW children due to greater need

for care. Thus, the main objective of this study was to

investigate whether the effects of LBW on presence and

severity of physical, developmental and psychological

outcomes (i.e. functional status) persist for children with a

medical home.

Methods

Study Design and Participants

A cross-sectional, secondary analysis of the 2007 National

Survey of Children’s Health (NSCH; N = 91,642) was

conducted. Eligible children were those 5 years old and

under (n = 27,566), whose mothers were the primary

respondents (n = 20,638), and who were not missing

birthweight data (n = 20,337).

Measures

Birthweight

Parental reported birthweight was standardized to ounces

in the publicly available dataset. If birthweight was less

than 88 oz (i.e. 2,500 g), the child was classified as LBW

(n = 1,638). All other children were NBW (n = 18,699).

Medical Home

Medical home was a calculated composite measure reflecting

five out of seven AAP criteria for a medical home (family-

centered, comprehensive, coordinated, compassionate, and

culturally effective), operationalized using 18 items. The

NSCH does not contain items measuring the accessible and

continuous medical home criteria. Tables describing items

used for each component and scoring algorithms can be

found at http://www.medicalhomedata.org and http://www.

nschdata.org [28, 29].

Children were classified as having a medical home if

they met all of the following criteria: (1) has a personal

doctor or nurse; (2) had a least one preventive medical visit

in the last year; (3) has no or few problems getting spe-

cialized care, services or equipment; (4) personal doctor or

nurse usually or always spends enough time with child and

communicates well; (5) child usually or always gets

immediate, needed care and advice from provider; (6)

personal doctor or nurse usually or always follows up if

child received specialized care, services, or equipment; and

(7) provider usually or always offered language services, if

needed.

Functional Status

Current functional status of children in this sample was

measured with five indicators: current developmental,

physical, and mental/behavioral health conditions; condi-

tion severity; and perceived overall health status. A list of

16 health conditions was used to ascertain presence of one

of the three types of conditions. To be classified as cur-

rently having one of the 16 health conditions, a mother

must have reported a positive diagnosis history from a

doctor and that the child currently suffers from the

condition.

For developmental and mental/behavioral conditions,

data were available only for children 2–5 year olds

(n = 13,120). A current developmental condition was

positive if parental report was yes to at least one of the

following: learning disability; Autism, Asperger’s Disor-

der, pervasive development disorder, or other autism

spectrum disorder; any developmental delay; or stuttering,

stammering or other speech problems. A mental/behavioral

condition was positive if the mother indicated one or more

of the following: Attention Deficit Hyperactive Disorder;

depression; anxiety problems; behavior or conduct prob-

lems; or Tourette Syndrome.

For presence of physical conditions and overall health

status, data were collected for all children. A child had a

S144 Matern Child Health J (2012) 16:S143–S150

123

current physical condition if the mother responded yes to

one or more of the following: asthma; diabetes; epilepsy or

seizure disorder; hearing problems; vision problems that

cannot be corrected; bone, joint or muscle problems; or a

brain injury or concussion. For overall health, mothers

were asked ‘‘In general, how would you describe your

child’s health?’’ Responses were grouped into tertiles: Poor

health (poor or fair), good health (good), or excellent health

(excellent or very good).

Condition severity was calculated only for those

children with one or more current conditions (n = 2,269).

For every positive maternal report of a current condition

out of the list of 16, the mother was asked to rate each as

mild, moderate or severe. If one or more of the condi-

tions was rated as severe, the child was classified as

having a severe condition. Otherwise, conditions were

not severe.

Covariates

Covariates included individual (child gender, insurance

status and race; maternal education, employment status and

poverty level), social (supportive neighborhoods), and

environmental (safe neighborhoods) characteristics. Chil-

dren had current health insurance coverage if the mother

answered yes to the question ‘‘Does your child have any

kind of health coverage, including health insurance, pre-

paid plans such as HMOs, or government plans such as

Medicaid?’’ Parental report of child race/ethnicity was

coded as White non-Hispanic, Black non-Hispanic, His-

panic, and Other. Mothers’ highest year of school com-

pleted was coded into less than high school, high school

graduate or GED, or more than high school. Mothers also

self-reported employment status based on whether anyone

in the household worked for at least 50 weeks out of the

last year. Poverty level was gathered from the federal

poverty level (FPL) indicator variable in the publicly

available data set, based on national guidelines [30]. Pov-

erty levels were coded as 100 % or less; 101–200,

201–400, and [400 %.

The supportive neighborhoods indicator (yes or no) was

a composite variable from responses to four questions

asking mothers to rate their agreement from 1 (Strongly

Agree) to 4 (Strongly Disagree) as to whether people in the

neighborhood help each other out, look out for each other’s

children, can count on others, and have trusting adults

nearby to help children if they get hurt or scared. If average

rating, calculated if at least two valid item responses were

available, was at or below the median threshold of 2.50,

children were coded as having a supportive neighborhood.

Children had a safe neighborhood if mothers indicated that

they usually or always felt that their children were safe in

the community or neighborhood.

Data Analysis

Data were weighted and analyzed using the complex sur-

vey methodology commands in Stata 11.0 to account for

non-response and non-coverage biases. All analyses were

conducted at an alpha of .05. Bivariate Chi-square analyses

examined the association of birthweight with medical

home, covariates, and outcomes. Logistic regression esti-

mated the relationship of birthweight and a medical home

to each of the three types of conditions and condition

severity. A proportional odds model was used to estimate

poorer overall health by birthweight and medical home.

This modeling technique was considered appropriate

because proportional odds assumptions were met. The

proportional odds assumption tests whether all logit sur-

faces are parallel for adjacent outcome categories. The

score Chi-square test at an a = 0.05 level was used, with

p [ .05 indicating validity of the proportional odds

assumption.

Adjusted odds ratios and 95 % confidence intervals for

the effects of medical home and birthweight were calcu-

lated using multivariable logistic and proportional odds

models, including medical home, birthweight, and all

covariates in the models. In order to test the presence of a

differential effect of birthweight by medical home, an

interaction term (medical home 9 birth weight) was added

to unadjusted and multivariable models, with its effect

tested using a t test. All analyses including the poverty

level variable were computed using the multiply imputed

poverty data files accompanying the 2007 NSCH and the

‘MI ESTIMATE: SVY’ command to avoid information

biases due to missing poverty data for eligible children

(n = 1,799, 8.9 %), as recommended by the methodology

report [30].

All variables except race and medical home had a\1 %

proportion of missing observations. About 1.5 % of obser-

vations for race and 2.5 % for medical home were missing.

In the total eligible sample (n = 20,337), about 981 cases

(4.8 %) were missing observations for any variable included

in analyses. Since the dataset was large and fewer than 5 %

of total cases were missing, analytic procedures were con-

sidered robust to non-response bias [31]. Missing values,

with the exception of poverty level, were not included in

analyses leaving a final sample size of 19,356.

Results

Table 1 shows that compared to NBW children, there was a

higher prevalence of LBW children who were female,

Black non-Hispanic or other race, and who were at 200 %

or below poverty level. Conversely, there was a lower

prevalence of LBW children who had anyone in the

Matern Child Health J (2012) 16:S143–S150 S145

123

household with continuous employment, had a medical

home, and who lived in a safe neighborhood compared to

NBW. There were no differences in health insurance cov-

erage, maternal education, or supportive neighborhoods.

Overall weighted prevalence estimates of functional

status outcomes were: physical health condition (8.9 %);

developmental condition (6.8 %); mental/behavioral con-

dition (2.4 %); severe condition, if any condition present

(41.6 %); and poor (2.5 %), good (10.4 %), or excellent

(87.2 %) health status. Table 2 shows that overall, LBW

had a higher prevalence than NBW of a physical condition

(15.2 vs. 8.3 %), developmental condition (11.1 vs. 6.4 %),

and fair/poor overall health (4.5 vs. 2.3 %). For children

without a medical home, Table 2 shows that LBW children

had a higher prevalence of a physical condition (20.8 vs.

11.2 %) and fair/poor overall health (7.0 vs. 4.1 %) than

NBW children. Similarly, for children with a medical

home, LBW children had a higher prevalence of physical

conditions than NBW children (10.5 vs. 6.9 %). Table 3

shows that although the effect of LBW was lessened for

those with a medical home for physical conditions, this

differential effect was non-significant (see Table 3,

LBW 9 medical home interaction p values).

Adjusted models containing the interaction term showed

that having a medical home did not modify the relationship

between LBW and physical (b = -0.27, SE = 0.31,

p = .39), developmental (b = 0.12, SE = 0.41, p = .78),

mental/behavioral (b = 0.60, SE = 0.69, p = .39), con-

dition severity (b = 0.64, SE = 0.43, p = .14), or poorer

overall health (b = -0.08, SE = 0.55, p = .89) outcomes.

Adjusted estimates of birthweight, both overall and by

medical home stratum, are shown in Table 4. Overall

estimates were computed using models without an inter-

action term. Regardless of having a medical home and

adjusting for all covariates, LBW is most strongly associ-

ated with an increased odds of a physical condition (AOR

1.7, CI 1.2–2.4), developmental condition (AOR 1.7, CI

1.1–2.6), and poorer overall health (AOR 1.5, CFI 1.1–2.1).

Table 4 also shows that having a medical home, indepen-

dent of birthweight, decreased the odds of all outcomes by

40–80 %. Adjusted effects for all other sociodemographic

covariates are presented in Table 4.

Discussion

Findings indicated that independent of having a medical

home, LBW children had on average a 70 % increased

odds of having a current physical or developmental con-

dition, and poorer rated overall health compared to NBW

children, consistent with previous findings [6–11]. How-

ever, in this sample of 0–5 year olds, LBW did not increase

the likelihood of mental/behavioral conditions or condi-

tions rated as severe. Previous studies found that LBW

increases the risk of depression, anxiety, and ADHD and

more severe chronic conditions [9–11], however, these

studies included samples of early to mid-adolescents (i.e.,

up to 12 or 16 years of age). Children in the current sample

could have been too young to have been identified as

having a mental/behavioral condition.

Findings also indicated that medical home was not an

effect modifier in the relationship between LBW and poor

outcomes. While previous studies have not tested this

effect modification directly, they do suggest that a medical

home may be particularly beneficial for high risk children

such as CSHCN [22–25]. Another example is the Infant

Health and Development Program (IHDP), a program

Table 1 Observed frequencies and weighted prevalence estimates of

selected covariates and functional status outcomes by birth weight,

children 0–5 years old, NSCH 2007 (N = 19,356)

Covariates NBW

(n = 17,804)

LBW

(n = 1,552)

p Value

n (%) n (%)

Child has medical home

(yes)

12,360 (66.0) 945 (54.6) \.001

Gender .007

Male 9,262 (52.3) 753 (43.6)

Female 8,542 (47.7) 799 (56.4)

Race/ethnicity .003

White, non-Hispanic 12,063 (57.1) 881 (47.0)

Black, non-Hispanic 1,417 (11.6) 244 (18.1)

Hispanic 2,662 (22.5) 258 (20.4)

Other 1,662 (8.8) 169 (14.5)

Health insurance coverage

(yes)

16,674 (91.9) 1,462 (94.2) .093

Maternal education .444

\High school 1,476 (12.6) 186 (15.5)

High school or GED 2,972 (23.7) 291 (23.3)

[High school 13,356 (63.7) 1,075 (61.2)

Anyone in household

employed C50/52 weeks

in past year (yes)

16,235 (89.1) 1,349 (85.1) .034

Poverty levela \.001

B100 2,293 (21.9) 323 (29.1)

101–200 2,975 (21.9) 271 (28.0)

201–400 5520 (28.6) 400 (22.2)

[400 5,679 (27.6) 431 (20.6)

Supportive neighborhood

(yes)

16,216 (89.0) 1,359 (86.3) .184

Safe neighborhood (yes) 15,612 (85.5) 1,302 (80.2) .045

NBW normal birth weight, LBW low birth weighta Derived indicator comparing income-to-household-size against

DHHS Federal Poverty Guidelines. Bivariate analysis conducted

using the multiply imputed poverty data file accompanying the 2007

NSCH dataset [30]. Observed frequencies are shown

S146 Matern Child Health J (2012) 16:S143–S150

123

related to the medical home concept used for LBW infants

that has been found to significantly improve cognitive,

behavioral, and physical health problems at age three up to

age eight [32, 33]. This study, though, found that having a

medical home was universally beneficial for LBW and

NBW children, supporting the Healthy People 2010 rec-

ommendation that all children should have a medical home

[19], as even children without a prior risk factor for poor

health outcomes such as LBW can benefit from medical

home utilization. However, this study is limited in that

outcomes may not have been robust enough to measure the

true impact of having a medical home, as a medical home

may not prevent the onset of health conditions but can

impact quality of life, symptom severity, and disease

management. Previous literature has indicated that the

effects of LBW can persist to young adulthood [12–16];

thus, it may be that medical home utilization in the longer

term may have an impact for higher risk youth and young

adults. Finally, literature [22] suggests that medical homes

reduce health disparities socially and economically. Future

research could test the interaction of socially and eco-

nomically related variables with medical home to assess its

relative advantage in improving health disparities.

Limitations

Since the study was cross-sectional, changes in the modi-

fying effect of medical home on the relationship between

birthweight and health outcomes over time could not be

assessed. Having a medical home may change the trajec-

tory of disease and condition management over time. A

longitudinal assessment and a more robust assessment of

disease and symptom course could help definitively

ascertain the true impact of having a medical home and

whether a differential impact exists based on prior bio-

logical risk factors such as LBW.

Table 2 Prevalence estimates of current functional status outcomes by low birth weight, stratified by medical home, children 0–5 years old,

NSCH 2007 (N = 19,356)

Outcome Overall (N = 19,356) Medical home—yes (n = 13,305) Medical home—no (n = 6,051)

NBW

n (%)

LBW

n (%)

p NBW

n (%)

LBW

n (%)

p NBW

n (%)

LBW

n (%)

p

Physical 1,317 (8.3) 244 (15.2) \.001 727 (6.9) 111 (10.5) .02 590 (11.2) 133 (20.8) .001

Developmentala 650 (6.4) 132 (11.1) .002 286 (4.0) 54 (6.6) .07 364 (10.7) 78 (16.2) .07

Mental/behaviorala 195 (2.2) 41 (4.1) .07 71 (0.9) 15 (2.3) .07 124 (4.8) 26 (6.1) .53

Condition severeb 739 (41.3) 155 (43.4) .71 316 (34.1) 65 (44.1) .18 423 (48.3) 90 (42.9) .50

Overall health .003 .39 .04

Fair/poor 300 (2.3) 61 (4.5) 100 (1.3) 17 (2.4) 200 (4.1) 44 (7.0)

Good 1,394 (10.0) 210 (14.1) 619 (6.7) 80 (7.0) 775 (16.4) 130 (22.7)

Excellent/very good 6,108 (87.7) 1,281 (81.4) 11,641 (92.0) 848 (90.6) 4,467 (79.5) 433 (70.3)

NBW normal birth weight, LBW low birth weighta For children age 2–5 years old (n = 12,508)b For children only with at least one current physical, mental/behavioral, or developmental condition (n = 2,164)

Table 3 Unadjusted odds ratios of current functional status outcomes by low birth weight, stratified by medical home, children 0–5 years old,

NSCH 2007 (N = 19,356)

Outcome Overall (N = 19,356) Medical home—yes (n = 13,305) Medical home—no (n = 6,051) LBW 9 medical homec

LBW OR (95 % CI) LBW OR (95 % CI) LBW OR (95 % CI) Unadjusted p

Physical 2.0 (1.5, 2.7) 1.6 (1.1, 2.4) 2.1 (1.3, 3.3) .40

Developmentala 1.8 (1.3, 2.7) 1.7 (0.9, 3.0) 1.6 (0.9, 2.7) .91

Mental/behaviorala 1.8 (0.9, 3.6) 2.6 (0.9, 7.9) 1.3 (0.6, 3.0) .31

Condition severeb 1.1 (0.7, 1.7) 1.5 (0.8, 2.8) 0.8 (0.4, 1.5) .15

Poorer overall health 2.0 (1.2, 3.4) 1.8 (0.7, 4.5) 1.8 (0.9, 3.4) .96

NBW normal birth weight, LBW low birth weight, OR = odds ratioa For children age 2–5 years old (n = 12,508)b For children only with at least one current physical, mental/behavioral, or developmental condition (n = 2,164)c Unadjusted regression models including a LBW 9 medical home interaction term

Matern Child Health J (2012) 16:S143–S150 S147

123

Data was also subject to measurement error. The pres-

ence of a current condition was self-reported and not val-

idated by medical records, so misclassification of health

outcomes could have been present. Also, mothers reporting

children as LBW may have been more likely to report a

current condition, overestimating the effect of birthweight

on outcomes. Additionally, the study only measured five

out of the seven components qualifying for the AAP defi-

nition of a medical home. Accessibility and continuity of

care were not measured, which may have caused non-

differential misclassification error, attenuating some effect

estimates.

Poverty, minority race/ethnicity, and lack of supportive

environments have been shown to be risk factors for poor

health outcomes and associated with both LBW and

accessible health care—a component of the medical home

not measured by the NSCH [34–38]. Although these social

determinants of health were included as covariates in

adjusted models, there may have been residual confound-

ing. Those mothers seeking and receiving care that meets

Table 4 Multivariable regression models for functional status outcomes, children 0–5 years old, NSCH 2007 (N = 19,356)

Covariates Outcomes

Physical Developmentalc Mental/behavioralc Condition severed Poorer overall healthe

AOR (95 % CI) AOR (95 % CI) AOR (95 % CI) AOR (95 % CI) AOR (95 % CI)

Low birth weight 9 medical homea

Medical home—low birth weight 1.5 (1.1, 2.2) 1.8 (1.1, 3.3) 2.3 (0.8, 6.9) 1.5 (0.8, 2.7) 1.6 (0.6, 3.9)

No medical home—low birth weight 2.0 (1.2, 3.1) 1.6 (0.9, 2.8) 1.3 (0.6, 2.9) 0.8 (0.4, 1.5) 1.7 (0.9, 3.2)

Birth weight (ref: normal)b

Low birth weight 1.7 (1.2, 2.4) 1.7 (1.1, 2.6) 1.5 (0.8, 3.0) 1.0 (0.6, 1.6) 1.5 (1.1, 2.1)

Medical home (ref: no)

Yes 0.6 (0.5, 0.8) 0.3 (0.2, 0.5) 0.2 (0.1, 0.4) 0.6 (0.4, 0.9) 0.5 (0.4, 0.7)

Gender (ref: female)

Male 1.5 (1.2, 2.0) 2.6 (1.9, 3.6) 1.5 (0.7, 3.1) 1.2 (0.8, 1.7) 1.1 (0.6, 1.9)

Race (ref: White)

Hispanic 0.6 (0.4, 0.8) 0.6 (0.3, 0.9) 0.5 (0.2, 1.3) 0.9 (0.5, 1.6) 2.1 (1.1, 4.4)

Black 1.7 (1.2, 2.4) 0.6 (0.3, 0.9) 0.2 (0.1, 0.5) 0.5 (0.3, 0.8) 2.0 (1.1, 3.6)

Other 1.0 (0.7, 1.5) 0.7 (0.4, 1.2) 0.7 (0.3, 1.5) 0.8 (0.5, 1.3) 2.4 (0.8, 7.5)

Health insurance coverage (ref: yes)

No 0.7 (0.4, 1.5) 0.4 (0.2, 0.8) 0.4 (0.1, 1.1) 0.3 (0.1, 0.8) 0.4 (0.2, 0.9)

Maternal education (ref: [high school)

\High school 1.2 (0.8, 1.8) 1.1 (0.6, 1.9) 1.4 (0.6, 3.3) 1.0 (0.5, 1.8) 1.6 (0.9, 2.8)

High school or GED 1.1 (0.8, 1.5) 1.0 (0.6, 1.6) 1.1 (0.6, 1.9) 1.0 (0.6, 1.6) 1.5 (0.8, 2.6)

Anyone in household employed C50 weeks in past year (ref: yes)

No 1.3 (0.9, 1.9) 1.5 (0.9, 2.5) 2.4 (1.2, 5.1) 1.6 (0.9, 2.8) 1.5 (0.8, 2.8)

Poverty level (ref: [400)

B100 1.5 (1.0, 2.2) 0.9 (0.5, 1.8) 2.3 (0.8, 6.7) 2.1 (1.1, 4.0) 1.3 (0.5, 3.2)

101–200 1.6 (1.1, 2.4) 1.2 (0.7, 2.0) 1.6 (0.5, 4.7) 1.8 (1.0, 3.3) 1.1 (0.4, 2.8)

201–400 1.2 (0.8, 1.7) 0.9 (0.5, 1.5) 0.9 (0.3, 2.4) 1.3 (0.7, 2.4) 0.7 (0.3, 1.7)

Supportive neighborhood (ref: yes)

No 1.1 (0.8, 1.5) 1.4 (0.8, 2.4) 2.1 (0.9, 4.8) 1.4 (0.8, 2.5) 2.1 (0.9, 4.7)

Safe neighborhood (ref: yes)

No 1.1 (0.8, 1.5) 1.8 (1.2, 2.8) 1.6 (0.8, 3.2) 0.9 (0.5, 1.4) 0.9 (0.5, 1.6)

AOR adjusted odds ratio, adjusted for all variables in the table, including lbw 9 medicalhome interaction, CI confidence intervala All lbw 9 medicalhome interaction terms were non-significant. Multiple imputation survey analysis tools within STATA 11.0 were used for

adjusted modelsb AOR for LBW and all other covariates were computed in models without the interaction term presentc For children age 2–5 years old (n = 12,508)d For children only with at least one current physical, mental/behavioral, or developmental condition (n = 2,164)e Ordinal logistic regression, modeling poorer health status

S148 Matern Child Health J (2012) 16:S143–S150

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criteria for a medical home may also have had unmeasured

characteristics related to better overall health for them-

selves and their children than mothers not reporting a

medical home.

Finally, the current study grouped VLBW and MLBW

children into one category of LBW due to smaller sample

size of VLBW children (n = 256). Estimates showed that if

VLBW and MLBW were examined separately, medical

home was not an effect modifier, but statistical power may

have been compromised by the small sample size. Also,

crude estimates showed that VLBW children have greatly

increased odds of a developmental, mental/behavioral, and

physical condition compared to NBW; these effects are

larger than if all LBW children were grouped together.

Future studies with a greater sample size of VLBW children

may be advantageous, as it is those children that would seem

to benefit the most from a medical home, due to care needs.

Conclusions

LBW compared to NBW children are more at risk for poorer

health outcomes during the first 5 years of life that may not

necessarily be differentially attenuated by the presence of a

medical home; yet, medical home may help with care and

symptom management over the lifecourse. Results sup-

porting a medical home for all children may provide impetus

to improve social and healthcare policies related to medical

insurance and access to care. Future research would benefit

from studying how different components of the medical

home affect health outcomes for children. Also, intervention

studies using the medical home can provide stronger evi-

dence for its effectiveness, which can further support a

standardized training program for medical professionals that

includes medical home concepts.

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