The Journal of School Nursing2021, Vol. 37(5) 396–403© The Author(s) 2019Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840519875506journals.sagepub.com/home/jsn
An underexamined consequence of childhood obesity is caregivers’ missed work attributed to child absence from school due to a health condition. This secondary analysis (N = 123) reported the frequency of missed work among caregivers of children with a body mass index (BMI) at or above the 75th percentile and examined associations with select child, parent, and household characteristics. Caregivers missed work 1.3 (SD = 1.2) times in the past year with 41% reporting 2 or more times. A child visiting a health-care provider 2 or more times in the past year and parent perception of their child’s health as good/fair/poor were significantly associated with caregivers’ missing work 2 or more times in a year (OR = 5.8 and OR = 3.0, respectively). A significant association between children’s physical and psychosocial well-being and caregivers’ missed work emphasizes the school nurse role working with children with high BMI and families to address student absenteeism and caregivers’ missed work.
missed work, school absence, school nursing, BMI, elementary
One in three children is classified as overweight or obese (Ogden, Carroll, Kit, & Flegal, 2014; Ogden et al., 2016), which is associated with an increased risk of physical comorbidities such as asthma, type 2 diabetes, hypertension, coronary heart diseases, and cancer (Park, Falconer, Viner, & Kinra, 2012). Childhood obesity may also affect psychological wellness, resulting in lower levels of perceived health and health-related quality of life (Halfon, Larson, & Slusser, 2013; Schwimmer, Burwinkle, & Varni, 2003; Williams, Wake, Hesketh, Maher, & Waters, 2005). These health-related consequences of childhood obesity lead to increased direct medical costs of US$12,660 to US$19,630 per child over a lifetime when compared to normal weight peers (Finkelstein, Graham, & Malhotra, 2014). Additionally, there are non-health-care costs associated with childhood obesity such as school absenteeism. Children who are overweight or obese are more likely to miss school days when compared to children with normal weight (An, Yan, Shi, & Yang, 2017; Li et al., 2012). School absenteeism negatively impacts students’ academic performance and graduation rates and may result in parents and/or other adult caregivers in the household (hereafter referred to collectively as caregivers) missing work to care for the child (Allen, Diamond-Myrsten, & Rollins, 2018).
Missed work among caregivers due to the health-related needs of a child is not unexpected. In 65% of families with school-aged children, both parents are employed (U.S. Department of Labor, 2017). Among employed mothers and fathers, 54% reported missing work in the past year to care for an ill child, with the average amount of missed work being 3.5 days (C.S. Mott Children’s Hospital, 2012). When caregivers miss work to care for an ill child, a reduction in family income and an increase in stress may occur (Hedov, Wikblad, & Annerén, 2006; Lindahl Norberg, Montgomery, Bottai, Heyman, & Hovén, 2017). Because overweight and obesity disproportionately impact minority and low-income populations (Ogden, Carroll, et al., 2018; Ogden, Fryar, et al., 2018), the potential impact of missed work on family well-being and by extension child well-being and school success may be even more pronounced. However, little is known about factors that may contribute to missed work among caregivers of children with a high body mass index (BMI), defined for the purpose of this study as a BMI at or above the 75th percentile. Therefore, the research questions addressed by the current exploratory study are (1) What is the frequency of missed work among a sample of caregivers of children with a high BMI? and (2) What are select child, parent, and household characteristics of caregivers associated with missed work? Independent variable selection was guided by a socioecological framework that recognizes factors that influence behavior choice occur at multiple levels, including child, parent, and household levels (Bronfenbrenner, 1994).
This secondary analysis used baseline data from the Students, Nurses and Parents Seeking Healthy Options Together (SNAPSHOT) study, a community-based randomized controlled trial conducted in metropolitan Minnesota. The study tested a school-based, school nurse-led healthy weight management program that aimed to prevent excess weight gain among 8- to 12-year-old children with a BMI at or above the 75th percentile (Kubik et al., 2018). Research suggests that young school-aged children with a BMI in the top quartile of the growth chart have an increased risk of excess weight gain, and interventions to prevent excess weight gain may be especially beneficial during this time (Datar, Shier, & Sturm, 2011; Nader et al., 2006).
Parent-child dyads were recruited from one urban and one suburban school district. Recruitment strategies included flyers, school and district website announcements, in-person presentations at school events, and general mailings. Interested parents were instructed to call study staff to determine eligibility that included child BMI ≥ 75th percentile, English literacy, participation of a parent/guardian with whom the participating child lived most of the time, no plans to move outside of the district within the next 12 months, no food allergies, no physical limitations or medical conditions that would limit child’s ability to participate in physical activity, and no emotional health conditions that would limit the child’s ability to participate in group activities with other children. A total of 132 parent-child dyads were enrolled in the SNAPSHOT study.
A team of two trained research staff collected baseline data in the summers of 2014–2017, prior to randomization and implementation of the intervention. All parents provided written informed consent for self and child, and children provided written assent before baseline data collection. Parent and child each completed a paper and pencil survey and had height and weight measured using standardized procedures that included collection of two or three measures to inform an averaged value (Lohman, Roche, & Martorell, 1988). Children also completed two 24-hr dietary recall interviews and wore an accelerometer as part of baseline data collection; however, these measures were not used in the present analyses. Details about measurement protocols are published elsewhere (Kubik et al., 2018). The parent and child received a $75 and a $50 retail gift card, respectively, for their participation in data collection. The Institutional Review Boards of the University of Minnesota and Temple University approved the study protocols.
A subset of measures was used in the current study that included anthropometry data and select items from the parent and child surveys.
Missed work. Parents answered the following question developed by the study investigators: “In the past year, how many times did you or any other adult in your home miss work because your child was unable to attend school due to a doctor’s appointment, an illness, or any other health condition?” Response options were never (0), 1 time (1), 2 times (2), and more than 2 times (3). These responses were dichotomized for analysis (<2 times vs. ≥2 times) based on the distribution of the responses in the sample.
Child demographics. Parents provided their child’s date of birth (age calculated), sex (female vs. male), race (White, Black, American Indian, Asian, and other), and ethnicity (Hispanic and non-Hispanic). Due to the small sample size, race/ethnicity was dichotomized as White versus non-White, which included all racial/ethnic backgrounds except for non-Hispanic White.
Child weight status. Child BMI (kg/m2) was calculated using measured height and weight. Child weight status was classified as obese (BMI ≥ 95th percentile) versus nonobese (BMI < 95th percentile) based on the BMI percentiles calculated using the 2,000 Centers for Disease Control and Prevention growth charts (Kuczmarski et al., 2002).
Child diagnosed health conditions. Parent reported whether their child had any diagnosed health conditions such as asthma, depression, and sleep problems (yes vs. no).
Number of visits to a health-care provider for an illness or health condition. Parents reported number of times their child was seen by a health-care provider in the past year for an illness or health conditions such as an ankle sprain, a cold, or a checkup for asthma (<2 times per year vs. ≥2 times per year).
Child-reported health-related quality of life. Children completed the 23-item Pediatric Quality of Life Inventory (PedsQL™) Version 4.0 Generic Core Scales designed for children 8–12 years of age (Varni, Seid, & Kurtin, 2001). The scale consisted of physical functioning (8 items), emotional functioning (5 items), social functioning (5 items), and school functioning (5 items) with a 5-point response option, including never (1), almost never (2), sometimes (3), often (4), and almost always (5). Following the scoring protocol (Varni et al., 2001), responses were reversed scored and transformed to a 0–100 scale (0, 25, 50, 75, 100) which were then used to calculate a total health-related quality of life summary score (mean of all 23 items), physical health summary score (mean of 8 physical functioning items), and psychosocial health summary score (mean of 15 emotional, social, and school functioning items). A higher score indicated better health-related quality of life. Cronbach’s α ranged from .69 to .89 in the current study.
Parent demographics. Parents provided their own date of birth (age calculated), sex (female vs. male), race (White, Black, American Indian, Asian, and other), and ethnicity (Hispanic and non-Hispanic). Similar to child race/ethnicity, parent race/ethnicity was dichotomized as White versus non-White. Parents also reported their marital status (married/partnered vs. single which included never married, separated, divorced, and spouse deceased), and employment status (employed vs. not employed).
Parent weight status. Parent BMI (kg/m2) was calculated using measured height and weight.
Parent concern about their child’s weight. It was dichotomized as “yes” (concerned and very concerned) or “no” (not concerned or a little concerned; Arcan et al., 2012).
Parent perception of their child’s health. It was assessed using five response options, including excellent, very good, good, fair, and poor (Zahner & Daskalakis, 1997). The response options were categorized as excellent or very good versus good, fair, or poor.
Parent-reported child health-related quality of life. Parents completed the parent-proxy version of the PedsQL™, which is identical to the child version of the scale except for the use of developmentally appropriate language or first- or third-person tense (Varni et al., 2001). Cronbach’s α ranged from .84 to .93 in the current study.
Receipt of public assistance. Parents reported receipt of free or reduced priced lunch, Supplemental Nutrition Assistance Program, and Electronic Benefits Transfer (no vs. yes if any).
Number of adults and children. Parents provided the number of adults (one adult, two adults, or ≥three adults) and children (one child vs. ≥ two children) in the household.
Household food insecurity. The 6-item short from of the U.S. Household Food Security Survey was used. A household was classified as food insecure if parent reported two or more affirmative responses to any of the 6 items (Blumberg, Bialostosky, Hamiltonm, & Briefel, 1999).
Of the 132 children enrolled in the SNAPSHOT study, 9 children with a BMI less than the 75th percentile at baseline measurement were excluded from analysis, which resulted in an analytic sample size of 123. Descriptive statistics were used to describe variables assessed as child-, parent-, and household-level characteristics. Bivariate analyses were used to inform the selection of independent variables to include in the regression model using a less conservative p ≤ .1 criterion given the small sample size and exploratory design of the study (Wasserstein & Lazar, 2016). Multivariate logistic regression was used to examine associations between the selected independent variables and caregivers’ missed work at p < .05. Analyses were performed using SAS software Version 9.3 (SAS Institute Inc., Cary, NC).
Child mean age was 9 years old, 49% were girls, 63% were non-White, and 51% were obese. Among parents, 59% reported the receipt of public assistance and 32% of households were classified as food insecure (Table 1). On average, parents reported that a caregiver missed work 1.3 (SD = 1.2) times in the past year, with 22% reporting missed work 1 time in the past year, 20% reporting 2 times, and 22% reporting 3 or more times. In bivariate analyses shown in Table 1, the following variables were associated with missed work among caregivers at p ≤ .1 and thus included in the multivariate logistic regression model: children who were diagnosed with asthma, children who had a history of visiting a health-care provider 2 or more times in the past year, parents who were concerned about their child’s weight, parents who perceived their child’s health as less than very good, parents who rated their child’s overall health-related quality of life lower, and households that had only one child. Multivariate logistic regression analyses (Table 2) indicated that parents whose child visited a health-care provider 2 times or more in the past year for an illness or health condition were almost 6 times more likely to report a caregiver in the household missing work than parents whose child visited a healthcare provider fewer than 2 times. Parents who reported their child had good, fair, or poor health were 3 times more likely to report a caregiver missing work than parents who reported their child’s health as very good or excellent.
Missed work among caregivers of children with a high BMI is an underexamined consequence of childhood obesity. In this sample of 8- to 12-year-old children with a BMI ≥75th percentile, 64% of caregivers missed work 1 or more times during the past year because their child was unable to attend school due to a doctor’s appointment, illness, or other health condition. More than one in five missed work 3 or more times. To the best of our knowledge, this is one of the first studies to report caregivers’ missed work by child weight status.
Two or more child visits to a health-care provider for an illness or health condition was significantly associated with caregivers’ missing work in the multivariate model after controlling for the effects of child-, parent-, and household-level characteristics on the dependent variable of caregivers’ missed work, which included child asthma diagnosis, parent concern about child’s weight, parent perceptions of their child’s health, parent-reported child health-related quality of life, and number of children in the household. A previous study suggested that children who are obese have an increase number of sick-child visits and use of mental health resources but fewer well-child visits compared to children who are overweight (Estabrooks & Shetterly, 2007). Our findings suggest that among 8- to 12-year-old children with a high BMI, 2 or more absences from school may be a prompt for school nurses to initiate a family assess-ment and determine whether referral to school and commu-nity preventive and social services may be indicated. School nurses have contributed to lowering school absenteeism among elementary students with asthma from 6 to 4 days by providing asthma screening and case management ser-vices (Moricca et al., 2013). A similar approach may be useful when addressing school absenteeism among children with a high BMI.
Not surprisingly, parental perceptions of their child’s health as poor, fair, or good was also associated with a caregivers’ missed work. This finding is consistent with the bivariate analyses results indicating the parent-reported psychosocial health summary score was significantly lower among children with a caregiver who missed work 2 times or more in the past year, compared to those who missed work less than 2 times. This difference provides insights into factors, such as emotional, social, and school functioning, that may contribute to parental perceptions of a child’s health status. Previous research has reported that children with high BMIs report psychosocial health scores that are typically lower than the physical health scores (Schwimmer et al., 2003; Williams et al., 2005). Children with a high BMI are also at risk of being bullied, which is associated with increased school absenteeism (Grinshteyn & Yang, 2017). These findings emphasize the importance of engaging parents when repeated school absences become a concern. Incorporating a holistic, compassionate approach informed by an awareness of the psychosocial challenges faced by some children who are overweight or obese, may lead to early interventions with the child and family and improvement in overall health and well-being, including improved child attendance at school and less missed work among caregivers.
It is interesting to note that we did not find any difference in caregivers’ missed work by child obesity status (obese vs. nonobese) in the current study. This may be a result of our sample size and focus on children with a BMI at or above the 75th percentile rather than the full range of BMI. Our approach is different from previous research that compared children with overweight or obesity to children with normal weight and showed a significant difference in school absenteeism between the two groups (An et al., 2017; Li et al., 2012). Future studies with a larger sample might examine whether caregivers’ missed work differs by child weight status, comparing across normal weight, overweight, and obese categories.
The study has several strengths. This is one of the first studies to examine child, parent, and household characteristics associated with missed work among caregivers of children with a BMI at or above the 75th percentile. The sample had economic and racial/ethnic diversity. Parent and child BMI were assessed using measured height and weight, and validated measures such as PedsQL™ and the U.S. Household Food Security Survey were used. However, the generalizability is limited because of our convenience sampling and small sample size. Furthermore, the current study was cross-sectional, and the findings do not indicate causality.
School nurses are well positioned to address student absenteeism among children with a high BMI, which may indirectly reduce missed work among caregivers. The interplay between student absenteeism and caregivers’ missed work suggests the importance of providing student-centered and family-focused school nursing care that is consistent with the Framework for 21st Century School Nursing Practice (National Assocation of School Nurses, 2016). For example, the framework principles of care coordination and leadership are represented by an approach whereby the school nurse initiates a comprehensive assessment of student health and parent concern about their child’s health when multiple absences are noted, such as two or more as demonstrated in the current study. In the role of advocate and liason for the child and family, the school nurse initiates referrals that support problem-solving of family situations that may contribute to student absenteeism and parent missed work that might include food insecurity, unreliable transportation, and housing instability (Allen et al., 2018). Within the broader school community and consistent with the principle of community/public health, school nurses are positioned to lead community-wide school campaigns that emphasize the link between student and family health, school attendance, and student success. The principle of quality improvement is served by careful documentation of all actions taken in support of students and families and evaluation of outcomes such as a decrease in absenteeism. In total, such efforts by school nurses will contribute to establishing an evidence base that exemplifies the unique contributions of school nurses to child and family health delivered in the school setting.
The content is solely the responsibility of the authors and does not necessarily represent the views of the National Institutes of Health.
All authors contributed to the conception of this manuscript and data analysis and interpretation. Jiwoo Lee prepared the draft of the manuscript, while all authors were involved in the critical revisions, gave final approval on the text, and agreed to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research study reported in this manuscript was supported by the National Institute of Nursing Research under Award Number R01NR013473 (M.Y. Kubik, PI, the SNAPSHOT study, National Clinical Trial number NCT02029976) of the National Institutes of Health.
Jiwoo Lee, PhD, RN https://orcid.org/0000-0003-2539-1098
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Jiwoo Lee, PhD, RN, is a research associate at the School of Nursing, University of Minnesota, Minneapolis, MN, USA.
Martha Y. Kubik, PhD, RN, is a professor at Department of Nursing, College of Public Health, Temple University, Philadelphia, PA, USA.
Jayne A. Fulkerson, PhD, is a professor at the School of Nursing, University of Minnesota, Minneapolis, MN, USA.
1 School of Nursing, University of Minnesota, Minneapolis, MN, USA
2 Department of Nursing, College of Public Health, Temple University, Philadelphia, PA, USA
3 School of Nursing, University of Minnesota, Minneapolis, MN, USA
Corresponding Author:Jiwoo Lee, PhD, RN, School of Nursing, University of Minnesota, 308 Harvard St. SE, Minneapolis, MN 55455, USA.Email: leex5222@umn.edu
