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Japan Journal of Nursing Science (2014) 11, 241–247
doi:10.1111/jjns.12025
ORIGINAL ARTICLE
Energy expenditure in preterm infants during periods of environmental stress in the neonatal intensive care unit Niang-Huei PENG,1 Jean BACHMAN,2 Chau-Huei CHEN,3 Li-Chi HUANG,4 Hong-Chin LIN5 and Tsai-Chung LI6 1
Nursing College, Central Taiwan University of Science and Technology, Taichung, 2College of Nursing, University of Missouri, St Louis, Missouri, USA, 3Chief of Division of Neonatology, Taichung Veterans General Hospital, 4School of Nursing, China Medical University, 5Division of Neonatology, China Medical University Hospital, 6Graduate Institution of Biostatistics, China Medical University, Taichung, Taiwan
Abstract Aim: To explore the energy expenditure (EE) in a group of preterm infants during the periods of environmental stress, and to explore the relationship between EE and physiological stress signals of preterm infants. Methods: Research design was an explorative secondary analysis of 4164 research data from 37 preterm infants which included physiological signals and environmental stressors in neonatal intensive care units. The current study investigated the data of EE calculated using heart-rate-based EE estimate. Results: A significantly positive relationship between EE and different levels of nursing intervention was found (P < 0.005). In addition, there was a significantly negative relationship between EE and oxygen saturation (P < 0.001). Conclusion: These research results confirmed that environmental stressors may impact the growth and developmental outcomes in preterm infants by increasing their EE. Neonatal clinicians should minimize excessive stimulations in order to conserve energy for the growth and developmental needs of preterm infants. Research found a significant relationship between an increase in EE and a decrease in oxygen saturation in preterm infants. The authors further hypothesized that EE of preterm infants may be predicted by estimating the oxygen saturation. Further study using different research methods and an enlarged sample size is needed. Key words: energy expenditure, environmental stress, neonatal intensive care units, preterm infants.
INTRODUCTION As the prognosis for survival of very low birthweight infants improves, awareness is being focused on their nutritional support. For preterm infants, current evidence reveals that differences in the early nutritional environment may have long-term consequences (Leitch & Denne, 2000). Moreover, stress caused by overstimulation of the immature neurological system of preterm Correspondence: Niang-Huei Peng, Nursing College, Central Taiwan University of Science and Technology, 666 Buzih Road, Beitun District, Taichung 40601, Taiwan. Email: [email protected] Received 22 October 2012; accepted 19 May 2013.
infants in the neonatal intensive care unit (NICU) may increase energy requirements for maintaining physiological homeostasis and promoting growth (Aita & Goulet, 2003; VandenBerg, 2007). For preterm infants, the energy requirement for normal growth is obviously higher than that for maintenance (Leitch & Denne, 2000). Neonatal stress leads to energy expenditure (EE), which may affect healing, recovery, and growth processes (Byers, 2003; Wilson, & McClue, 1994). Researchers have proposed that light, noise, touch stimulation, handling, and caregiving interventions are the main environmental stressors for preterm infants in the NICU which may interrupt preterm infants’ energy conservation (Nair, Gupta, & Jatana, 2003;
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
N.-H. Peng et al.
Japan Journal of Nursing Science (2014) 11, 241–247
VandenBerg, 2007). However, there is little research confirming the increased EE of preterm infants during the periods of environmental stress. Heart-rate (HR) monitoring, or HR-based EE estimate, is the described EE estimation method, based on a well-known relationship between cardiorespiratory function and measured EE (Firstbeat Technologies Ltd, 2007). According to the Fick principle, the cardiac output (HR × stroke volume) is defined as the ratio of oxygen consumption to the arteriovenous oxygen difference and suggests a possible relation between HR and oxygen consumption (Achten & Jeukendrup, 2003). Studies have provided evidence for a linear relationship between HR and oxygen consumption (Achten & Jeukendrup, 2003; Gastinger, Sorel, Nicolas, Gratas-Delamarche, & Prioux, 2010; Keytel et al., 2005; Livingstone et al., 1992; Woodson, Field & Greenberg, 1983). A regression line is derived from simultaneous measurements of the mean HR, and different levels of EE can be calculated for the period of investigation (Beghin et al., 2002; Leitch & Denne, 2000; Payne, Wheeler, & Salvosa, 1971). The usual measurement of EE requires complicated equipment which may affect the subject’s environmental and behavioral pattern, making it impractical for a routine clinical investigation. On the other hand, HR-based EE estimate gives an accurate estimate of total EE and is convenient for examining the EE during specific activities or intense exercise sessions (Beghin et al., 2000; Chessex et al., 1981). The validity and reliability of HR-based EE estimate has been verified against reference methods such as the doubly-labeled water method (Beghin et al., 2000; Chessex et al., 1981) and whole-body indirect calorimetry (Bitar et al., 1996; Treuth, Adolph, & Butte, 1998). Moreover, researchers have defined the relationship between HR and metabolic rate in newborn infants, and evaluated the accuracy of prediction of metabolic rate from HR (Beghin et al., 2000; Chessex et al., 1981). Chessex et al. (1981) have performed 35 studies in 16 infants to evaluate the relationship between the metabolic rate (cal/kg × min) and HR (b.p.m.) compared minute by minute. Their research revealed a significant and close relationship between HR and metabolic rate, and a close linear regression relationship was found when HR exceeded 140 b.p.m. Several investigations on the total EE of healthy children have been done in a broader spectrum of populations using minute-by-minute HR monitoring (Cessay et al., 1989; Davidson, NcNeill, Haggarty, Smith, & Franklin, 1997; Livingstone et al., 1992). Pierro et al. (1994) have also developed an equation by using minute-by-minute
242
HR monitoring for predicting total EE in stable surgical infants. In this present investigation, the authors measured the EE of preterm infants during periods of environmental stress in the NICU using the method of HR-based EE estimate.
RESEARCH PURPOSE The purposes of this exploratory secondary analysis were to examine the conditions of EE in preterm infants during periods of environmental stress in the NICU, and to explore the relationships between EE and changes in respiratory rate and oxygen saturation.
ETHICAL CONSIDERATION The institutional review board of the research hospital approved the study protocol for this secondary analysis. For the original study, the institutional review board of the University of Missouri, St Louis, and hospitals in central Taiwan approved the study protocol, and written parental consent was obtained (Peng et al., 2009).
RESEARCH METHODS This study was an explorative secondary analysis of data from a previous study examining the relationships between environmental stressors and biobehavioral responses in one group of preterm infants using a prospective repeated-measure design (Peng et al., 2009). The current study investigated EE calculated using the HR of preterm infants during periods of environmental stress.
Sample and setting The research settings were two level III NICU at two teaching hospitals in a city in central Taiwan. Inclusion criteria for the secondary analysis were: (i) having being born at less than 37 weeks of gestational age; (ii) age of less than 28 days at the time of the study; (iii) in an incubator at the time of the study; and (iv) having complete demographic data and physical monitoring data at the entry and exit of the original study. Exclusion criteria were: (i) preterm infants with major health complications (i.e. chronic lung disease, necrotizing enterocolitis, and serious infectious diseases); (ii) preterm infants with congenital anomalies, hemorrhagic/ ischemic white matter brain injuries above level III, or
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
Japan Journal of Nursing Science (2014) 11, 241–247
needing surgery; and (iii) preterm infants using mechanical ventilation (i.e. intermittent positive pressure ventilation, high-frequency ventilation), phototherapy, and sedative medicines at the time of study. Thirty-seven preterm infants fitted the research sampling criteria and participated in the original study from 2007 to 2008 (Peng et al., 2009).
RELIABILITY AND VALIDITY OF MEASUREMENT Measurements of research data In the original study, environmental stressors were defined as increased levels of sound or light in the preterm infant’s environment, including nursing interventions that increase light and/or sound levels, and handling stimulation. A Likert-type scale was used to measure the degree of uncomfortable stimulation in nursing interventions. In addition, a TES-1336 photometer (Macam Photometrics, Livingston, Scotland) was used to measure light levels in the incubator. The accuracy of the TES-1336 is ±(3% rdg + 5dgts). A Rion NL-10A phonometer was used to measure sound levels in the incubator. The device used was certified for accuracy at the factory prior to being used in this research. A Likert-type scale was used to measure the degree of stimulation in nursing interventions and classified by levels: level 0, no intervention; level 1, interventions that include noise or light stimulation; level 2, interventions that include noise and light stimulation; level 3, interventions that include noise or light and handling stimulation; level 4, interventions that include noise, light, and handling stimulation; level 5, any intervention that causes pain. Physiological signals for this investigation were HR, respiratory rate (RR), and oxygen saturation. In the original study, examination of the relationship between physiological stress signals and environmental stress was one of the research purposes. Operationally, assessment of the stress physiological signals was measured by a cardiorespiratory monitor to determine heart and RR and oxygen saturation. The operational definitions of physiological stress signals were as follows: (i) HR of less than 100 b.p.m. or more than 160 b.p.m., or an increase in baseline of 5 b.p.m. or more; (ii) irregular RR of less than 40 or more than 60 breaths/min, or an increase in baseline of 7 breaths/min or more; and (iii) oxygen saturation of less than 90% or a decrease of 2.5% or more.
Energy expenditure in preterm infants
The principle of HR-based EE estimates was used to calculate the average EE every 2 min based on the HR of the preterm infants.
DATA COLLECTION Research variables were measured every 2 min during four 60 min observation periods conducted over 2 research days. Environmental stressors included sound level, light illumination, and the degree of uncomfortable stimulation in nursing interventions as measured by the phonometer and photometer as well as recorded by the research nurse. The physiological signals were measured by a cardiorespiratory monitor and information was subsequently transmitted to the research computer in order to calculate the averaged HR, RR, oxygen saturation every 2 min, and EE rate averaged over a time frame. The EE of the preterm infants was calculated by the following equation (Chessex et al., 1981):
Energy expenditure per heart beat (cal kg × beat ) = mean metabolic rate × duration of study (min) / accumulated heart beats; Y = −0.0000291 X3 + 0.01685 X 2 − 2.93X + 197 (Y = metabolic rate; X = heart beats) . In this secondary analysis, the mean HR each 2 min was used to predict the average EE rate of the preterm infants.
DATA ANALYSIS Descriptive statistics were used to characterize the sample. Mean of HR, RR, oxygen saturation, and EE in preterm infants for all periods of environmental stress were analyzed by the generalized estimating equation (GEE) method’s multiple linear regressions. All analyses were performed with SPSS ver. 19.0 for Window (SPSS, Chicago, IL, USA). P < 0.05 was considered statistically significant.
RESULTS Distribution of demographic data Research data were 4164 repeat-measure recordings from 37 preterm infants. Of these research subjects, 18 (48.6%) were female and 19 (51.4%) were male. Mean gestational age (GA) was 32.05 weeks with a range of 27–36 weeks. Mean birth bodyweight (BBW) was 1662.35 g with a range of 890.00–2655.00 g. The mean
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
243
N.-H. Peng et al.
Japan Journal of Nursing Science (2014) 11, 241–247
Relationships between research variables and changes in EE
Apgar score at 1 min was 6 with a range of 1–9. The mean Apgar score at 5 min was 8 with a range of 5–10. The mean bodyweight (BW) upon entry into the study was 1673.24 g with a range of 890–2655 g. Environmental stressors included increased sound, light, and nursing interventions occurring in the incubator with nursing interventions classified into five levels. A total of 342 nursing interventions were counted during research time. A baseline measure of light (mean = 0.324 footcandles [ft-c]) and sound (mean = 52.56 dB) was recorded 3822 times when no intervention was occurring. The range of light illumination was 0.94–2.3 ft-c and the range of sound was 56.12–63.62 dB during different levels of nursing interventions. In the original study, the mean HR was 148.53 b.p.m. (mode, 150 b.p.m.; standard deviation [SD], 17.22) and the mean RR was 46.33 breaths/min (mode, 30 breaths/ min; SD, 14.77). The mean oxygen saturation was 96.97%. The average EE was 39.32 cal/kg (SD, 2.78) with a range of 36.91–62.7 cal/kg averaged over a time frame. Table 1 shows the research data description.
Research data were analyzed by generalized lineal model with GEE by specifying identity link function. Table 2 expresses the relationships between EE and various research variables. After adjusting for the effects of other factors (birth age, sex, GA, BBW, BW), there was a significantly positive relationship between EE and different levels of nursing intervention (intervention 2, P = 0.01; intervention 3, P < 0.0001; intervention 4, P < 0.000; intervention 5, P = 0.0 2). More specifically, the EE for nursing intervention level 2 (average, 0.94 units; mean, 40.68 cal/kg averaged over a time frame), level 3 (average, 2.05 units; mean, 41.45 cal/kg averaged over a time frame), level 4 (average, 2.42 units; mean, 42.5 cal/kg averaged over a time frame), and level 5 (average, 3.07 units; mean, 43.96 cal/kg averaged over a time frame) were higher than for no intervention status, after adjusting for the effects of other factors (Table 2). In addition, there was a significantly negative
Table 1 Research data description Demographic data (n = 37, female = 18, male = 19; measurements = 4164) Variables Birthweight (g) Study initial weight (g) Gestational age (weeks)
Mean
Range
SD
1662.351 1673.243 32.059
950.00–2635.00 890.00–2635.00 27–36
327.707 300.324 2.208
Stressors Environmental stressors Light (ft-c) Sound level (dB) Physiological signals Stress physiological signals Heart rate (b.p.m.) Respiratory rate (breaths) Oxygen saturation (mg%)
Mean SS Mean SD Mean 148.53 46.33 96.97
Interventions
No interventions
1.48 1.69 58.94 7.57
0.32 0.52 52.56 4.47
Mode 150 30 100
SD 17.22 14.77 3.53
Energy expenditure (cal/kg per min) Levels of interventions
Mean
Confidence interval
SD
Level Level Level Level Level Level
39.13 41.67 40.67 41.44 42.50 43.95
(39.053–39.216) (40.02–43.327) (40.067–41.285) (40.719–42.715) (41.084–43.916) (41.491–46.425)
0.04 0.81 0.31 0.37 0.69 1.09
0 1 2 3 4 5
ft-c, foot-candles; SD, standard deviation.
244
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
Japan Journal of Nursing Science (2014) 11, 241–247
Energy expenditure in preterm infants
Table 2 Relationships of the energy expenditure and independent variables (n = 4164 repeated measurements) Variables †
Intercept Oxygen saturation RR (60)‡ Times Light Sound level Intervention 5§ Intervention 4§ Intervention 3§ Intervention 2§ Intervention 1§ Sex female¶ Birth age GA BBW BW
Parameter estimate
Standard error
95% confidence interval
Z
P-value
62.449 −0.073 0.163 0.007 0.027 0.0003 3.071 2.416 2.045 0.943 1.138 −0.127 −0.032 −0.022 −0.002 −0.001
6.103 0.021 0.115 0.009 0.109 0.0004 1.279 0.666 0.433 0.371 0.93 0.231 0.073 0.182 0.003 0.003
(50.487 to 74.411) (−0.115 to −0.031) (−0.062 to 0.388) (−0.011 to 0.024) (−0.187 to 0.241) (−0.0005 to 0.001) (−5.577 to −0.565) (−3.72 to −1.111) (−2.895 to −1.196) (−1.67 to −0.216) (−2.959 to 0.684) (−0.58 to 0.327) (−0.174 to 0.11) (−0.379 to 0.334) (−0.008 to 0.003) (−0.008 to 0.006)
10.23 −3.41 1.42 0.75 0.24 0.69 −2.4 −3.63 −4.72 −2.54 −1.22 −0.55 −0.44 −0.12 −0.81 −0.32
0.00
Japan Journal of Nursing Science (2014) 11, 241–247
doi:10.1111/jjns.12025
ORIGINAL ARTICLE
Energy expenditure in preterm infants during periods of environmental stress in the neonatal intensive care unit Niang-Huei PENG,1 Jean BACHMAN,2 Chau-Huei CHEN,3 Li-Chi HUANG,4 Hong-Chin LIN5 and Tsai-Chung LI6 1
Nursing College, Central Taiwan University of Science and Technology, Taichung, 2College of Nursing, University of Missouri, St Louis, Missouri, USA, 3Chief of Division of Neonatology, Taichung Veterans General Hospital, 4School of Nursing, China Medical University, 5Division of Neonatology, China Medical University Hospital, 6Graduate Institution of Biostatistics, China Medical University, Taichung, Taiwan
Abstract Aim: To explore the energy expenditure (EE) in a group of preterm infants during the periods of environmental stress, and to explore the relationship between EE and physiological stress signals of preterm infants. Methods: Research design was an explorative secondary analysis of 4164 research data from 37 preterm infants which included physiological signals and environmental stressors in neonatal intensive care units. The current study investigated the data of EE calculated using heart-rate-based EE estimate. Results: A significantly positive relationship between EE and different levels of nursing intervention was found (P < 0.005). In addition, there was a significantly negative relationship between EE and oxygen saturation (P < 0.001). Conclusion: These research results confirmed that environmental stressors may impact the growth and developmental outcomes in preterm infants by increasing their EE. Neonatal clinicians should minimize excessive stimulations in order to conserve energy for the growth and developmental needs of preterm infants. Research found a significant relationship between an increase in EE and a decrease in oxygen saturation in preterm infants. The authors further hypothesized that EE of preterm infants may be predicted by estimating the oxygen saturation. Further study using different research methods and an enlarged sample size is needed. Key words: energy expenditure, environmental stress, neonatal intensive care units, preterm infants.
INTRODUCTION As the prognosis for survival of very low birthweight infants improves, awareness is being focused on their nutritional support. For preterm infants, current evidence reveals that differences in the early nutritional environment may have long-term consequences (Leitch & Denne, 2000). Moreover, stress caused by overstimulation of the immature neurological system of preterm Correspondence: Niang-Huei Peng, Nursing College, Central Taiwan University of Science and Technology, 666 Buzih Road, Beitun District, Taichung 40601, Taiwan. Email: [email protected] Received 22 October 2012; accepted 19 May 2013.
infants in the neonatal intensive care unit (NICU) may increase energy requirements for maintaining physiological homeostasis and promoting growth (Aita & Goulet, 2003; VandenBerg, 2007). For preterm infants, the energy requirement for normal growth is obviously higher than that for maintenance (Leitch & Denne, 2000). Neonatal stress leads to energy expenditure (EE), which may affect healing, recovery, and growth processes (Byers, 2003; Wilson, & McClue, 1994). Researchers have proposed that light, noise, touch stimulation, handling, and caregiving interventions are the main environmental stressors for preterm infants in the NICU which may interrupt preterm infants’ energy conservation (Nair, Gupta, & Jatana, 2003;
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
N.-H. Peng et al.
Japan Journal of Nursing Science (2014) 11, 241–247
VandenBerg, 2007). However, there is little research confirming the increased EE of preterm infants during the periods of environmental stress. Heart-rate (HR) monitoring, or HR-based EE estimate, is the described EE estimation method, based on a well-known relationship between cardiorespiratory function and measured EE (Firstbeat Technologies Ltd, 2007). According to the Fick principle, the cardiac output (HR × stroke volume) is defined as the ratio of oxygen consumption to the arteriovenous oxygen difference and suggests a possible relation between HR and oxygen consumption (Achten & Jeukendrup, 2003). Studies have provided evidence for a linear relationship between HR and oxygen consumption (Achten & Jeukendrup, 2003; Gastinger, Sorel, Nicolas, Gratas-Delamarche, & Prioux, 2010; Keytel et al., 2005; Livingstone et al., 1992; Woodson, Field & Greenberg, 1983). A regression line is derived from simultaneous measurements of the mean HR, and different levels of EE can be calculated for the period of investigation (Beghin et al., 2002; Leitch & Denne, 2000; Payne, Wheeler, & Salvosa, 1971). The usual measurement of EE requires complicated equipment which may affect the subject’s environmental and behavioral pattern, making it impractical for a routine clinical investigation. On the other hand, HR-based EE estimate gives an accurate estimate of total EE and is convenient for examining the EE during specific activities or intense exercise sessions (Beghin et al., 2000; Chessex et al., 1981). The validity and reliability of HR-based EE estimate has been verified against reference methods such as the doubly-labeled water method (Beghin et al., 2000; Chessex et al., 1981) and whole-body indirect calorimetry (Bitar et al., 1996; Treuth, Adolph, & Butte, 1998). Moreover, researchers have defined the relationship between HR and metabolic rate in newborn infants, and evaluated the accuracy of prediction of metabolic rate from HR (Beghin et al., 2000; Chessex et al., 1981). Chessex et al. (1981) have performed 35 studies in 16 infants to evaluate the relationship between the metabolic rate (cal/kg × min) and HR (b.p.m.) compared minute by minute. Their research revealed a significant and close relationship between HR and metabolic rate, and a close linear regression relationship was found when HR exceeded 140 b.p.m. Several investigations on the total EE of healthy children have been done in a broader spectrum of populations using minute-by-minute HR monitoring (Cessay et al., 1989; Davidson, NcNeill, Haggarty, Smith, & Franklin, 1997; Livingstone et al., 1992). Pierro et al. (1994) have also developed an equation by using minute-by-minute
242
HR monitoring for predicting total EE in stable surgical infants. In this present investigation, the authors measured the EE of preterm infants during periods of environmental stress in the NICU using the method of HR-based EE estimate.
RESEARCH PURPOSE The purposes of this exploratory secondary analysis were to examine the conditions of EE in preterm infants during periods of environmental stress in the NICU, and to explore the relationships between EE and changes in respiratory rate and oxygen saturation.
ETHICAL CONSIDERATION The institutional review board of the research hospital approved the study protocol for this secondary analysis. For the original study, the institutional review board of the University of Missouri, St Louis, and hospitals in central Taiwan approved the study protocol, and written parental consent was obtained (Peng et al., 2009).
RESEARCH METHODS This study was an explorative secondary analysis of data from a previous study examining the relationships between environmental stressors and biobehavioral responses in one group of preterm infants using a prospective repeated-measure design (Peng et al., 2009). The current study investigated EE calculated using the HR of preterm infants during periods of environmental stress.
Sample and setting The research settings were two level III NICU at two teaching hospitals in a city in central Taiwan. Inclusion criteria for the secondary analysis were: (i) having being born at less than 37 weeks of gestational age; (ii) age of less than 28 days at the time of the study; (iii) in an incubator at the time of the study; and (iv) having complete demographic data and physical monitoring data at the entry and exit of the original study. Exclusion criteria were: (i) preterm infants with major health complications (i.e. chronic lung disease, necrotizing enterocolitis, and serious infectious diseases); (ii) preterm infants with congenital anomalies, hemorrhagic/ ischemic white matter brain injuries above level III, or
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
Japan Journal of Nursing Science (2014) 11, 241–247
needing surgery; and (iii) preterm infants using mechanical ventilation (i.e. intermittent positive pressure ventilation, high-frequency ventilation), phototherapy, and sedative medicines at the time of study. Thirty-seven preterm infants fitted the research sampling criteria and participated in the original study from 2007 to 2008 (Peng et al., 2009).
RELIABILITY AND VALIDITY OF MEASUREMENT Measurements of research data In the original study, environmental stressors were defined as increased levels of sound or light in the preterm infant’s environment, including nursing interventions that increase light and/or sound levels, and handling stimulation. A Likert-type scale was used to measure the degree of uncomfortable stimulation in nursing interventions. In addition, a TES-1336 photometer (Macam Photometrics, Livingston, Scotland) was used to measure light levels in the incubator. The accuracy of the TES-1336 is ±(3% rdg + 5dgts). A Rion NL-10A phonometer was used to measure sound levels in the incubator. The device used was certified for accuracy at the factory prior to being used in this research. A Likert-type scale was used to measure the degree of stimulation in nursing interventions and classified by levels: level 0, no intervention; level 1, interventions that include noise or light stimulation; level 2, interventions that include noise and light stimulation; level 3, interventions that include noise or light and handling stimulation; level 4, interventions that include noise, light, and handling stimulation; level 5, any intervention that causes pain. Physiological signals for this investigation were HR, respiratory rate (RR), and oxygen saturation. In the original study, examination of the relationship between physiological stress signals and environmental stress was one of the research purposes. Operationally, assessment of the stress physiological signals was measured by a cardiorespiratory monitor to determine heart and RR and oxygen saturation. The operational definitions of physiological stress signals were as follows: (i) HR of less than 100 b.p.m. or more than 160 b.p.m., or an increase in baseline of 5 b.p.m. or more; (ii) irregular RR of less than 40 or more than 60 breaths/min, or an increase in baseline of 7 breaths/min or more; and (iii) oxygen saturation of less than 90% or a decrease of 2.5% or more.
Energy expenditure in preterm infants
The principle of HR-based EE estimates was used to calculate the average EE every 2 min based on the HR of the preterm infants.
DATA COLLECTION Research variables were measured every 2 min during four 60 min observation periods conducted over 2 research days. Environmental stressors included sound level, light illumination, and the degree of uncomfortable stimulation in nursing interventions as measured by the phonometer and photometer as well as recorded by the research nurse. The physiological signals were measured by a cardiorespiratory monitor and information was subsequently transmitted to the research computer in order to calculate the averaged HR, RR, oxygen saturation every 2 min, and EE rate averaged over a time frame. The EE of the preterm infants was calculated by the following equation (Chessex et al., 1981):
Energy expenditure per heart beat (cal kg × beat ) = mean metabolic rate × duration of study (min) / accumulated heart beats; Y = −0.0000291 X3 + 0.01685 X 2 − 2.93X + 197 (Y = metabolic rate; X = heart beats) . In this secondary analysis, the mean HR each 2 min was used to predict the average EE rate of the preterm infants.
DATA ANALYSIS Descriptive statistics were used to characterize the sample. Mean of HR, RR, oxygen saturation, and EE in preterm infants for all periods of environmental stress were analyzed by the generalized estimating equation (GEE) method’s multiple linear regressions. All analyses were performed with SPSS ver. 19.0 for Window (SPSS, Chicago, IL, USA). P < 0.05 was considered statistically significant.
RESULTS Distribution of demographic data Research data were 4164 repeat-measure recordings from 37 preterm infants. Of these research subjects, 18 (48.6%) were female and 19 (51.4%) were male. Mean gestational age (GA) was 32.05 weeks with a range of 27–36 weeks. Mean birth bodyweight (BBW) was 1662.35 g with a range of 890.00–2655.00 g. The mean
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
243
N.-H. Peng et al.
Japan Journal of Nursing Science (2014) 11, 241–247
Relationships between research variables and changes in EE
Apgar score at 1 min was 6 with a range of 1–9. The mean Apgar score at 5 min was 8 with a range of 5–10. The mean bodyweight (BW) upon entry into the study was 1673.24 g with a range of 890–2655 g. Environmental stressors included increased sound, light, and nursing interventions occurring in the incubator with nursing interventions classified into five levels. A total of 342 nursing interventions were counted during research time. A baseline measure of light (mean = 0.324 footcandles [ft-c]) and sound (mean = 52.56 dB) was recorded 3822 times when no intervention was occurring. The range of light illumination was 0.94–2.3 ft-c and the range of sound was 56.12–63.62 dB during different levels of nursing interventions. In the original study, the mean HR was 148.53 b.p.m. (mode, 150 b.p.m.; standard deviation [SD], 17.22) and the mean RR was 46.33 breaths/min (mode, 30 breaths/ min; SD, 14.77). The mean oxygen saturation was 96.97%. The average EE was 39.32 cal/kg (SD, 2.78) with a range of 36.91–62.7 cal/kg averaged over a time frame. Table 1 shows the research data description.
Research data were analyzed by generalized lineal model with GEE by specifying identity link function. Table 2 expresses the relationships between EE and various research variables. After adjusting for the effects of other factors (birth age, sex, GA, BBW, BW), there was a significantly positive relationship between EE and different levels of nursing intervention (intervention 2, P = 0.01; intervention 3, P < 0.0001; intervention 4, P < 0.000; intervention 5, P = 0.0 2). More specifically, the EE for nursing intervention level 2 (average, 0.94 units; mean, 40.68 cal/kg averaged over a time frame), level 3 (average, 2.05 units; mean, 41.45 cal/kg averaged over a time frame), level 4 (average, 2.42 units; mean, 42.5 cal/kg averaged over a time frame), and level 5 (average, 3.07 units; mean, 43.96 cal/kg averaged over a time frame) were higher than for no intervention status, after adjusting for the effects of other factors (Table 2). In addition, there was a significantly negative
Table 1 Research data description Demographic data (n = 37, female = 18, male = 19; measurements = 4164) Variables Birthweight (g) Study initial weight (g) Gestational age (weeks)
Mean
Range
SD
1662.351 1673.243 32.059
950.00–2635.00 890.00–2635.00 27–36
327.707 300.324 2.208
Stressors Environmental stressors Light (ft-c) Sound level (dB) Physiological signals Stress physiological signals Heart rate (b.p.m.) Respiratory rate (breaths) Oxygen saturation (mg%)
Mean SS Mean SD Mean 148.53 46.33 96.97
Interventions
No interventions
1.48 1.69 58.94 7.57
0.32 0.52 52.56 4.47
Mode 150 30 100
SD 17.22 14.77 3.53
Energy expenditure (cal/kg per min) Levels of interventions
Mean
Confidence interval
SD
Level Level Level Level Level Level
39.13 41.67 40.67 41.44 42.50 43.95
(39.053–39.216) (40.02–43.327) (40.067–41.285) (40.719–42.715) (41.084–43.916) (41.491–46.425)
0.04 0.81 0.31 0.37 0.69 1.09
0 1 2 3 4 5
ft-c, foot-candles; SD, standard deviation.
244
© 2013 The Authors Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science
Japan Journal of Nursing Science (2014) 11, 241–247
Energy expenditure in preterm infants
Table 2 Relationships of the energy expenditure and independent variables (n = 4164 repeated measurements) Variables †
Intercept Oxygen saturation RR (60)‡ Times Light Sound level Intervention 5§ Intervention 4§ Intervention 3§ Intervention 2§ Intervention 1§ Sex female¶ Birth age GA BBW BW
Parameter estimate
Standard error
95% confidence interval
Z
P-value
62.449 −0.073 0.163 0.007 0.027 0.0003 3.071 2.416 2.045 0.943 1.138 −0.127 −0.032 −0.022 −0.002 −0.001
6.103 0.021 0.115 0.009 0.109 0.0004 1.279 0.666 0.433 0.371 0.93 0.231 0.073 0.182 0.003 0.003
(50.487 to 74.411) (−0.115 to −0.031) (−0.062 to 0.388) (−0.011 to 0.024) (−0.187 to 0.241) (−0.0005 to 0.001) (−5.577 to −0.565) (−3.72 to −1.111) (−2.895 to −1.196) (−1.67 to −0.216) (−2.959 to 0.684) (−0.58 to 0.327) (−0.174 to 0.11) (−0.379 to 0.334) (−0.008 to 0.003) (−0.008 to 0.006)
10.23 −3.41 1.42 0.75 0.24 0.69 −2.4 −3.63 −4.72 −2.54 −1.22 −0.55 −0.44 −0.12 −0.81 −0.32
0.00
