Correlations in Siblings' Physical Activity and Sedentary Behavior: Results from the Hispanic Community Children's Health Study/Study of Latino Youth

Abstract

Background:

Family is an important determinant of youth's health behaviors, yet research on the importance of intragenerational relationships for determining physical activity (PA) and sedentary behaviors (SBs) is limited. This study examined correlations in siblings' total PA, moderate-to-vigorous physical activity (MVPA), and SB and explored potential determinants of differences in Hispanic/Latino siblings' activity.

Methods:

Hispanic/Latino 8–16-year olds from the cross-sectional Hispanic Community Children's Health Study/Study of Latino Youth with ≥1 sibling enrolled were examined (n = 535). Activity was assessed using the Actical accelerometer. Linear mixed models were used with total PA, MVPA, or SB as the outcome; correlations among siblings' PA and SB were assessed with intraclass correlation coefficients (ICCs).

Results:

ICCs for siblings' total PA, MVPA, and SB were 0.26 (95% confidence interval: 0.16–0.36), 0.29 (0.21–0.38), and 0.42 (0.34–0.51), respectively. There were no differences in correlations between siblings who were all brothers compared to all sisters. However, compared to siblings of differing sexes, siblings who were all brothers had the strongest correlations in total PA (0.61 [0.46–0.76]) and MVPA (0.64 [0.49–0.78]), and siblings who were all sisters had the weakest correlations in SB (0.14 [−0.10 to 0.37]). Correlations did not differ according to age, and social and environmental measures did not explain differences in siblings' PA or SB.

Conclusions:

Correlations in Hispanic/Latino siblings' PA and SB ranged from slight to fair, with siblings who were all brothers generally having the strongest correlations. Future research should examine determinants of sex-specific differences in siblings' PA and SB correlations.

Introduction

The Physical Activity Guidelines for Americans recommend that youth aged 6 to 17 years complete at least 60 minutes of moderate-to-vigorous physical activity (MVPA) daily,¹ and the World Health Organization further recommends that youth limit the time spent in sedentary behaviors (SBs), particularly recreational screen time.² However, youth in the United States do not meet these recommendations, with a lower percent of Hispanic/Latino vs. non-Hispanic White adolescents meeting the recommended daily MVPA (25.8% vs. 27.1%) and a higher percent of Hispanic/Latino vs. non-Hispanic White adolescents watching TV for ≥3 hours/day on an average school day (20.7% vs. 17.7%).³ Given that low physical activity (PA) levels and high engagement with SB are associated with increased risk of obesity and related cardiometabolic disease,^4,5 there is a need to identify means of increasing total PA, particularly MVPA, and decreasing SB among Hispanic/Latino youth.

Family is an important determinant of health behaviors in youth, with parent, sibling, and extended family relationships having the potential to influence PA and SB.⁶ Sibling relationships are particularly important as they tend to be the longest lasting relationship among family members (in terms of life expectancy).^7–9 Further, siblings uniquely influence one another's health behaviors as trusted friends/peers and teachers/role models,^9–11 which may make them key influencers of PA and SB. However, existing sibling PA and SB research is limited and has primarily been conducted in non-Hispanic White populations.⁹ Importantly, findings from these studies have limited generalizability to Hispanic/Latino youth given the cultural differences in family dynamics and relationships.^12,13 Thus, research addressing the role of siblings in determining Hispanic/Latino youth's PA and SB is needed.^6,9

To our knowledge, only three studies of similarities in Hispanic/Latino siblings' PA have been conducted in the United States,^12,14,15 two of which also examined SB^12,14 and all of which used subjective activity measures.^12,14,15 Although there were consistent positive associations for siblings' SB, both positive and null associations were reported for siblings' MVPA, indicating a need for further research.^12,14,15 There is also a need to clarify the role that siblings' sex concordance^12,16–18 and age difference¹⁹ may have in the strength of correlations to better understand whether engaging siblings can help create and maintain behavior change.

While shared environments in siblings are expected to promote similarities in siblings' PA and SB, there is also a need to identify the nonshared social and physical environments of siblings that may be impacting PA and SB. In doing so, future interventions can target these modifiable measures to promote successful behavior change.

The objective of this study is to examine correlations in siblings' objectively measured total PA, MVPA, and SB and, secondarily, to determine whether social and environmental measures explain differences in these measures. We hypothesized that siblings' PA and SB correlations would be stronger among siblings closer in age and of the same sex, and that individuals who reported greater friend support for PA, greater availability of after-school PA opportunities, and greater availability/use of workout equipment at home than their siblings would have higher PA and lower SB.

Methods

Study Population

The Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth) is a cross-sectional, ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).^20,21 HCHS/SOL is a prospective cohort study of 16,415 self-identified Hispanic/Latino adults (aged 18–74 years) from four communities in the United States (Bronx, NY; Chicago, IL; Miami, FL; San Diego, CA).^20,21 Between 2012 and 2014, SOL Youth²² enrolled 1466 youth aged 8–16 years living in the household of a parent/caregiver who completed the HCHS/SOL baseline examination (2008–2011). All siblings living in the same household and between these ages were eligible for SOL Youth. Protocols for HCHS/SOL and SOL Youth were approved by the institutional review boards of each institution participating in the study and are published elsewhere.^20–22 Written informed consent and assent were obtained from parents and youth, respectively.

Measures

PA and SB

Frequency, duration, and intensity of PA were assessed using the Actical (Philips Respironics, Bend, OR) accelerometer (version B-1, model 198-0200-03). Youth were instructed to wear the accelerometer over their right hip using a waist strap for seven continuous days. The accelerometer was only to be removed for swimming, showering, and sleeping. Adherence to accelerometer protocol was defined as ≥8 hours of wear time for at least three days and did not require inclusion of a weekend day.²³

Epoch length was set to 15 seconds, and nonwear time was defined as consecutive zero counts for ≥90 minutes, allowing for short time intervals with nonzero counts ≤2 minutes if no counts were detected 30 minutes upstream and downstream from that interval. Data were summarized as average accelerometer counts per minute. PA and SB thresholds were based on a prior calibration study of the Actical accelerometer: sedentary 0–17 counts/epoch; light activity, 18–440 counts/epoch; moderate activity, 441–872 counts/epoch; and vigorous activity ≥873 counts/epoch.²⁴

Social and Environmental Determinants.

Friend support for PA

Friend support for PA was assessed using five items from a 16-item questionnaire on family and friend support for diet and PA.^25,26 Individuals indicated, using 5-point Likert-type responses, the number of days a friend was supportive/unsupportive of their PA during the past week (1 = “never” to 5 = “everyday”). The one item on “teasing” was reverse-coded, and individuals received a mean score across the five items (range: 1–5 [least to most supportive]; Cronbach's α = 0.65).

After-school PA environment

The after-school PA environment was assessed with 5-point Likert-type responses for two items: “How often does your school have supervised PA after-school?” and, “How often does your school allow students to use play areas or fields after-school?”²⁷ Responses were dichotomized as never/rarely/sometimes and mostly/always.²⁷ Items were assessed separately in all analyses.

Workout equipment use at home

The availability and frequency of use of workout equipment at home were assessed with 5-point Likert-type responses to an 11-item questionnaire.²⁸ Individuals reported if specific equipment was available at home and the number of times per week they typically used the equipment. Responses were collapsed such that individuals received a score of 0 if the workout equipment was unavailable, 1 if the item was available and they never used it, and 2 if it was available and they used it at all. Individuals then received a total score equaling the sum of responses across the 11 items (range: 0–22; Cronbach's α = 0.71).

Covariates

Covariates for this analysis were child-reported age, sex, nativity, and Hispanic/Latino background; parent-reported annual household income, number of individuals living in the household (excluding the participating parent), and educational attainment; and SOL Youth site.

Statistical Analysis

Of the 1466 youth, 792 had at least one other sibling enrolled in the study, of which 610 were adherent to the accelerometer protocol. We excluded 34 individuals who were missing sociodemographic information and an additional 41 individuals who did not have at least one sibling in the analytic data set after applying the aforementioned accelerometer adherence requirement and exclusion criterion. The final analytic sample size was 535 youth.

Linear mixed models were used to determine correlations in siblings' PA and SB. Separate models were analyzed using total PA, MVPA (moderate PA and vigorous PA also examined separately), or SB as the outcome. In all models, a random intercept representing the effect of family was included, and a variance component covariance model was used for optimum model fit (as measured by the Akaike information criterion [AIC]). All covariates were included as fixed effects in all models. Intraclass correlation coefficients (ICCs) were calculated from the mixed models to assess the degree of correlation in siblings' PA.²⁹ ICCs were interpreted according to the guidelines by Shrout³⁰: virtually no similarity = 0.00–0.10; slight = 0.11–0.40; fair = 0.41–0.60; moderate = 0.61–0.80; and substantial similarity = 0.81–1.00. ICCs were statistically significant if the 95% confidence interval (CI) did not include the null hypothesis (ICC = 0.00).

To calculate CIs for each ICC, a cluster bootstrap procedure (with “family” as the cluster) was conducted for 5000 iterations, and the standard deviation of the bootstrapped distribution was used to calculate the CIs.

To examine whether correlations in PA and SB varied according to sex, analyses were stratified based on if all siblings in the analytic sample were brothers, sisters, or a combination of both. To determine whether correlations differed according to age, age differences were assigned to each sibling in a family relative to the youngest sibling in the analytic sample. Analyses were stratified based on if all siblings in the analytic sample were <3 years vs. ≥3 years apart in age. Three years was selected as the cut point, given it was the median “maximum age difference in siblings sets,” similar to the approach used in other studies.^19,31 The same bootstrap approach described above was used to calculate 95% CIs for each ICC. Significant differences in sibling correlations according to sex concordance or age difference were based on whether the 95% CIs overlapped for the stratified ICCs.

To explore whether potential differences in siblings' PA and SB were explained by differences in siblings' friend support for PA, the after-school PA environment, or workout equipment use at home, these variables were added into the models together as additional fixed effects. Significance was set at p < 0.05 for all analyses. All analyses were conducted in SAS software version 9.4 (SAS Institute).

Results

Among the 535 individuals, 68.4% had one sibling, 24.7% had two siblings, and 6.9% had at least three siblings included in this analysis. Youth were primarily 12–16 years of age (53.1%), female (51.6%), and from households with ≤$20,000 annual income (55.1%; Table 1). The most frequently reported Hispanic/Latino background was Mexican (47.5%), and most youth were born in the United States' 50 states/District of Columbia (DC) (79.4%; Table 1).

Table 1.

Characteristics of the Analytic Sample of Siblings from the Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth) (n = 535)

	Mean (SD) or n (%)
Child's age group, years
8–11	251 (46.9)
12–16	284 (53.1)
Child's sex
Female	276 (51.6)
Male	259 (48.4)
Child's Hispanic/Latino background
Dominican	65 (12.1)
Central American	30 (5.6)
Cuban	37 (6.9)
Mexican	254 (47.5)
Puerto Rican	44 (8.2)
South American	17 (3.2)
Mixed/Other	88 (16.4)
SOL Youth site
Bronx	157 (29.3)
Chicago	163 (30.5)
Miami	90 (16.8)
San Diego	125 (23.4)
Child's nativity
Born in a United States territory or foreign country	110 (20.6)
Born in the United States' 50 states/District of Columbia (DC)	425 (79.4)
Parental education^a
<HS or GED	99 (41.9)
HS or GED	66 (28.0)
>HS or GED	71 (30.1)
Household income^a
≤$20,000	130 (55.1)
>$20,000 to <$40,000	72 (30.5)
≥$40,000	34 (14.4)
Household size^a	4.0 (1.5)
Child's BMI, kg/m²	21.9 (6.5)
Child's BMI percentile	70.2 (29.1)
Friend support for PA (range: 1–5)	3.2 (0.9)
After-school PA environment
Supervised PA after-school (mostly/always)	312 (58.3)
Play areas available after-school (mostly/always)	292 (54.6)
Workout equipment use at home (range: 0–22)	8.9 (4.9)

Parent-reported (n = 236 parents).

BMI, body mass index; GED, General Educational Development; HS, high school; PA, physical activity; SOL Youth, Hispanic Community Children's Health Study/Study of Latino Youth.

On average, youth accumulated 35.9 minutes/day of MVPA and 599.4 minutes/day of SB (Table 2). This equated to 10.8% of the analytic sample meeting the United States' MVPA guidelines. Overall, there was “fair” correlation in siblings' SB (0.42 [95% CI: 0.34–0.51]) and “slight” correlations in siblings' total PA (0.26 [0.16–0.36]) and MVPA (0.29 [0.21–0.38]; Table 2).

Table 2.

Means and Intraclass Correlation Coefficients (ICC [95% Confidence Interval]) for Association of Total Physical Activity (PA), Moderate-to-Vigorous Physical Activity (MVPA), and Sedentary Behavior (SB) Among Siblings in the Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth), Overall and Stratified by Sex (n = 535)

	Overall (n = 535)	Sex-specific analyses
	Overall (n = 535)	Sisters (n = 114)	Brothers (n = 98)	Sisters–brothers (n = 323)
Mean (SD)
Total PA, counts/minute	257.4 (125.5)	244.6 (119.4)	266.8 (140.0)	259.1 (123.4)
MVPA, minutes/day	35.9 (21.0)	33.0 (17.2)	37.3 (23.6)	36.4 (21.4)
Moderate PA	25.7 (13.0)	24.7 (10.8)	25.8 (13.1)	26.2 (13.8)
Vigorous PA	10.1 (9.6)	8.3 (8.6)	11.6 (12.1)	10.3 (9.0)
SB, minutes/day	599.4 (110.6)	597.8 (121.6)	597.9 (100.4)	600.5 (110.0)
ICC
Total PA	0.26 (0.16 to 0.36)	0.19 (−0.10 to 0.49)^ab	0.61 (0.46 to 0.76)^a	0.22 (0.11 to 0.34)^b
MVPA	0.29 (0.21 to 0.38)	0.38 (0.18 to 0.59)^ab	0.64 (0.49 to 0.78)^a	0.20 (0.10 to 0.31)^b
Moderate PA	0.30 (0.22 to 0.39)	0.28 (0.07 to 0.48)^ab	0.59 (0.41 to 0.76)^a	0.28 (0.17 to 0.38)^b
Vigorous PA	0.26 (0.15 to 0.37)	0.34 (0.01 to 0.68)^ab	0.62 (0.48 to 0.77)^a	0.10 (0.00 to 0.20)^b
SB	0.42 (0.34 to 0.51)	0.14 (−0.10 to 0.37)^a	0.45 (0.21 to 0.68)^ab	0.53 (0.44 to 0.63)^b

ICCs with different superscripts are significantly different from each other.

All ICCs are from linear mixed models adjusted for youth's age (continuous), youth's sex (male vs. female [ref]), youth's Hispanic/Latino background (Dominican, Central American, Cuban, Mexican [ref], Puerto Rican, South American, Mixed/Other), SOL Youth site (Bronx [ref], Chicago, Miami, San Diego), youth's nativity (United States' 50 states/District of Columbia [DC] [ref] vs. United States territory or foreign country), parent's education (<high school [ref], high school or GED, >high school), household income (≤$20,000 [ref], >$20,000 to <$40,000, ≥$40,000), and household size (continuous) as fixed effects and family as a random intercept.

Sedentary, <17 counts/15 seconds; moderate PA, 441–872 counts/15 seconds; vigorous PA, ≥873 counts/15 seconds; MVPA, ≥441 counts/15 seconds.

ICC, intraclass correlation coefficient; MVPA, moderate-to-vigorous physical activity; PA, physical activity; SB, sedentary behavior.

When analyses were stratified according to siblings' sex concordance, we observed significant differences in siblings' total PA, MVPA, and SB for siblings who were all brothers or all sisters relative to siblings of differing sexes (Table 2). Notably, siblings who were all brothers had stronger correlations in total PA (0.61 [0.46–0.76]) and MVPA (0.64 [0.49–0.78]) compared to siblings of differing sexes (total PA: 0.22 [0.11–0.34]; MVPA: 0.20 [0.10–0.31]; Table 2). In addition, siblings who were all sisters had lower correlations in SB (0.14 [−0.10 to 0.37]) compared to siblings of differing sexes (0.53 [0.44–0.63]; Table 2).

Correlations for PA and SB did not significantly differ between siblings who were all brothers compared to all sisters (Table 2) or according to age difference (Supplementary Table S1). Differences in siblings' friend support for PA, the after-school PA environment, and workout equipment use at home did not explain differences in siblings' PA or SB (Table 3).

Table 3.

Beta Coefficients (95% Confidence Interval) for Association of Differences in Siblings' Social and Environmental Determinants with Siblings' Total Physical Activity (PA), Moderate-to-Vigorous Physical Activity (MVPA), and Sedentary Behavior (SB) in the Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth) (n = 519)

	Friend support for PA	Supervised PA after-school	Play areas available after-school	Workout equipment use at home
Total PA, counts/minute	11.18 (−1.35 to 23.72)	15.78 (−6.20 to 37.75)	−5.91 (−26.72 to 14.90)	0.71 (−1.46 to 2.88)
MVPA, minutes/day	1.84 (−0.30 to 3.98)	2.93 (−0.82 to 6.68)	−0.84 (−4.39 to 2.71)	0.05 (−0.32 to 0.42)
Moderate PA	1.05 (−0.29 to 2.38)	1.62 (−0.71 to 3.96)	−0.30 (−2.51 to 1.92)	−0.01 (−0.24 to 0.22)
Vigorous PA	0.80 (−0.20 to 1.80)	1.30 (−0.46 to 3.05)	−0.56 (−2.22 to 1.10)	0.06 (−0.11 to 0.24)
SB, minutes/day	−2.37 (−12.56 to 7.83)	4.47 (−13.17 to 22.11)	−2.31 (−19.11 to 14.50)	−0.75 (−2.53 to 1.02)

All coefficients are from linear mixed models adjusted for youth's age (continuous), youth's sex (male vs. female [ref]), youth's Hispanic/Latino background (Dominican, Central American, Cuban, Mexican [ref], Puerto Rican, South American, Mixed/Other), SOL Youth site (Bronx [ref], Chicago, Miami, San Diego), youth's nativity (United States' 50 states/District of Columbia [DC] [ref] vs. United States territory or foreign country), parent's education (<high school [ref], high school or GED, >high school), household income (≤$20,000 [ref], >$20,000 to <$40,000, ≥$40,000), household size (continuous), friend support for PA (continuous), supervised PA after-school (never/rarely/sometimes [ref] vs. mostly/always), play areas available after-school (never/rarely/sometimes [ref] vs. mostly/always), and workout equipment use at home (continuous) as fixed effects and family as a random intercept.

Sedentary, <17 counts/15 seconds; moderate PA, 441–872 counts/15 seconds; vigorous PA, ≥873 counts/15 seconds; MVPA, ≥441 counts/15 seconds.

Sample size is 519 instead of 535 due to missing data for the social and environmental measures.

MVPA, moderate-to-vigorous physical activity; PA, physical activity; SB, sedentary behavior.

Discussion

In this study of pre-adolescent and adolescent siblings from diverse Hispanic/Latino backgrounds, we found that total PA, MVPA, and SB were correlated among siblings, with the strongest correlations for SB. Compared to siblings of differing sexes, siblings who were all brothers had the strongest correlations in total PA and MVPA, and siblings who were all sisters had the weakest correlations in SB. There were no differences in correlations in PA or SB between siblings who were all brothers compared to all sisters or according to siblings' age gap. Further, differences in social and environmental measures were not associated with differences in siblings' PA or SB.

This study builds on previous publications that have described activity and associations with cardiometabolic health in SOL Youth.^4,23 To our knowledge, this is the first study in any Hispanic/Latino population to examine correlations in siblings' objectively measured PA and SB. In line with our hypothesis, total PA, MVPA, and SB were significantly correlated among siblings in the overall sample. Previous qualitative studies of Hispanic/Latino youth have indicated that siblings can positively influence each other's activity through means such as co-participating, role-modeling, providing social support, chaperoning, or providing transportation to recreational activities outside their neighborhoods.^32,33 However, siblings can also hinder each other's PA by promoting increased engagement with SB.³⁴

In our sample, Hispanic/Latino siblings' correlations in both SB and PA were significant, consistent with findings from two previous studies from the United States.^12,15 Further, correlations were stronger for SB compared to PA, similar to a third previous study conducted in Hispanic/Latino siblings in the Unites States that found significant correlations for SB but not MVPA.¹⁴ The previous study may not have reported a significant correlation for MVPA as we did due to examining a multiethnic sample of 58 sibling dyads, of which only 11 were Hispanic/Latino. Cultural differences in their sample may have promoted different levels of familial support for activity^12,13 and, thus, null associations in siblings' PA. Differences in PA assessments may also explain the discrepant MVPA findings, given we used an objective measure while the previous authors used a self-report measure¹⁴ not utilized in the other studies.^12,15

We also observed that correlations in siblings' PA differed according to sex concordance but not age difference. The results for age difference are in contrast with our hypothesis and a previous study of non-Hispanic/Latino youth,³¹ suggesting that age difference may be of greater relevance for predicting similarities in siblings' PA in non-Hispanic/Latino youth vs. Hispanic/Latino youth. Consistent with our hypothesis that PA correlations would be strongest for same-sex sibling sets, we found that brothers had the strongest correlations in total PA and MVPA compared to siblings of differing sexes and that there were no significant differences in correlations between all-brother vs. all-sister sibling sets. Opposite to our expectations, siblings who were all sisters had lower correlations in SB relative to siblings of differing sexes.

One potential explanation for stronger SB but not PA correlations among siblings of differing sexes is that there are fewer barriers to co-participation in SB. For example, siblings of opposite sexes can watch TV or play on computers together but may not participate in the same club or team sports due to teams being restricted to one sex only or due to differing sports interests³⁵ or performance abilities.³⁶ We explored correlations in types of SB (self-reported), but we did not find that one particular activity was more strongly correlated than others among siblings of differing sexes (Supplementary Table S2). Thus, future research should examine why SB was specifically stronger among siblings of differing sexes relative to all-sister but not all-brother sibling sets and the types of SB that sibling sets most frequently engage in together.

Only one study in the United States has examined the role of sex concordance in Hispanic/Latino siblings' PA and SB, reporting significant associations in SB and PA for brother–brother dyads but not sister–sister or sister–brother dyads.¹² Although our findings are similar to this study from the United States, they are in contrast with other studies conducted in Portugal where the strongest correlations in total PA were for sister–sister pairs (0.26–0.53) followed by brother–sister (0.24–0.37) and then brother–brother pairs (0.18–0.34)^16–18—similar, although less consistent, trends were also reported for sport and leisure activity indices,^17,18,37 which map to MVPA and SB in our study, respectively. Future research should thus examine the relationship qualities that may be driving sex-specific differences in siblings' PA correlations.⁹ This research should consider the moderating role of role-modeling, involvement in similar activities,³⁸ engagement in activity-related competition/rivalry,³⁹ and social support for PA.⁶

Finally, to examine potential explanations for differences in siblings' PA, we looked at whether differences in siblings' social and built environments could explain differences in siblings' PA. In contrast with our hypothesis, we did not find that any of these measures explained differences in youth's PA or SB. We explored whether strongly overlapping social and built environments may explain this finding; however, siblings' responses largely differed for each measure (Supplementary Table S3). Thus, a more likely explanation for our null findings is that these measures are not key determinants of PA and SB for this sample or that they lack construct specificity for SB.

Strengths and Limitations

This study has many strengths, including the examination of a diverse group of Hispanic/Latino youth across four cities in the United States. We used objective measures of PA and SB for both siblings, in contrast to previous studies that have largely focused on PA and relied on self-report measures or collected data from the perspective of one child or parent only. Extensive data were collected by trained interviewers and examiners, allowing us to assess novel social and environmental determinants of siblings' activity.

Despite the study's strengths, there are some limitations. We do not know if the siblings examined in this study were biologically related, and we are unable to adjust for birth order due to all siblings not being enrolled in SOL Youth and not collecting these data otherwise. In addition, 182 eligible individuals were excluded from the present analysis due to noncompliance to accelerometer protocol. In a previous SOL Youth analysis, we reported that accelerometer adherence was lower among youth of Puerto Rican and South American backgrounds and among older age groups,²³ which may have biased our current findings. However, the percentage of SOL Youth participants considered non-adherent to accelerometer protocol is largely consistent with that of previous studies.^40,41

The timing of data collection could also have impacted sibling correlations or contributed to atypical data on friend/school-based interactions (e.g., during summer months vs. school year; weekend vs. weekday). However, SOL Youth enrollment was distributed across the year—with siblings completing questionnaires around the same time—and >97% of the analytic sample's accelerometer data included at least one weekend day. Lastly, the effect of PA and SB of siblings not enrolled in SOL Youth or otherwise excluded from this analysis was not assessed but could impact siblings' correlations (see Supplementary Table S4 for a comparison of the analytic sample with the full SOL Youth sample).

Conclusions

In the present study, Hispanic/Latino siblings' total PA, MVPA, and SB were significantly correlated, with siblings who were all brothers having the strongest correlations in total PA and MVPA. This study contributes to existing literature by suggesting that future interventions aimed at increasing PA and decreasing SB in Hispanic/Latino youth in the United States include siblings in their studies.

Impact Statement

To our knowledge, this is the first study to report correlations in Hispanic/Latino siblings' objectively measured PA and SB. Findings indicate that sex, rather than age, is an important determinant of correlations in siblings' activity, with siblings who are all brothers having the strongest correlations in PA.

Footnotes

Authors' Contributions

M.N.L.: Conceptualization, formal analysis, methodology, software, visualization, and writing—original draft; K.R.E.: Conceptualization, data curation, and writing—reviewing and editing; K.M.P.: Data curation, funding acquisition, and writing—reviewing and editing; L.V.H.: Funding acquisition and writing—reviewing and editing; X.X.: Methodology and writing—reviewing and editing; L.C.G.: Funding acquisition and writing—reviewing and editing; M.L.D.: Funding acquisition and writing—reviewing and editing; C.R.I.: Conceptualization, funding acquisition, resources, supervision, and writing—reviewing and editing.

Disclaimer

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Heart, Lung, and Blood Institute (NHLBI) or the National Institutes of Health.

Funding Information

The Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth) was supported by grant R01HL102130 from the NHLBI. The children in SOL Youth are drawn from the study of adults, the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). HCHS/SOL is a collaborative study supported by contracts from the NHLBI to the University of North Carolina (HHSN268201300001I/N01-HC-65233), University of Miami (HHSN268201300004I/N01-HC-65234), Albert Einstein College of Medicine (HHSN268201300002I/N01-HC-65235), University of Illinois at Chicago (HHSN268201300003I/N01-HC-65236 Northwestern University), and San Diego State University (HHSN268201300005I/N01-HC-65237). The following Institutes/Centers/Offices have contributed to HCHS/SOL through a transfer of funds to the NHLBI: National Institute on Minority Health and Health Disparities, National Institute on Deafness and Other Communication Disorders, National Institute of Dental and Craniofacial Research, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, and National Institutes of Health (NIH) Office of Dietary Supplements.

Additional support was provided by the Life Course Methodology Core (LCMC) at Albert Einstein College of Medicine and the New York Regional Center for Diabetes Translation Research (P30 DK111022-8786 and P30 DK111022) through funds from the National Institute of Diabetes and Digestive and Kidney Diseases. Support for the lead author was provided by an NHLBI training grant (T32HL144456).

Author Disclosure Statement

No competing financial interests exist.

Supplementary Material

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