Occup Environ Med. 2015 Mar;72(3):208-15.

Lifetime shift work exposure: association with anthropometry, body composition, blood pressure, glucose and heart rate variability.

Breno Bernardes Souza1, Nayara Mussi Monteze2, Fernando Luiz Pereira de Oliveira3, José Magalhães de Oliveira4, Silvia Nascimento de Freitas2, Raimundo Marques do Nascimento Neto1, Maria Lilian Sales5, Gabriela Guerra Leal Souza6

1School of Medicine, Federal University of Ouro Preto, Ouro Preto, Brazil

2School of Nutrition, Federal University of Ouro Preto, Ouro Preto, Brazil

3Department of Statistics,Federal University of Ouro Preto, Ouro Preto, Brazil

4Institute of Psychiatry, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

5São Paulo State Cancer Institute, São Paulo, Brazil

6Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil

 

ABSTRACT

Objective: To evaluate the association between lifetime exposure to shift work and blood pressure, fasting glucose (FG), anthropometric variables, body composition and heart rate variability (HRV).

Methods: Male shift workers (N=438) were evaluated using principal component (PC) analysis. The variables used were: weight, body mass index (BMI), waist circumference (WC), neck circumference (NC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to height ratio (WHtR), body fat mass (BFKg), body fat percentage (BF%), visceral fat area (VFA), FG, systolic (SBP) and diastolic blood pressure (DBP), and HRV variables. ECG was performed, extracting heart rate (HR), root mean square of the successive differences (RMSSD), high frequency (HF), low frequency (LF) and the LF/HF ratio. Using linear regression models, the lifetime shift work exposure was associated with each PC.

Results: Five PCs were obtained, which accounted for 79.6% of the total variation of the data. PC1 (weight, BMI, WC, NC, HC, WHR, WHtR, BFKg, BF% and VFA) was designated as body obesity; PC2 (HF, RMSSD and LF) as good cardiac regulation; PC3 (SBP and DBP) as blood pressure; PC4 (LF/HF ratio and HR) as bad cardiac regulation and PC5 (WHR and FG) as insulin resistance. After age adjustment, the regression analysis showed that lifetime shift work was negatively associated with PC2 and positively associated with PC3.

Conclusions: The association of lifetime shift work exposure with PC2 and PC3 suggests that shift work promotes unfavourable changes in autonomic cardiac control related to a decrease in parasympathetic modulation and an increase in blood pressure.

KEYWORDS: cardiac autonomic control; principal component analysis

PMID: 25540411

 

SUPPLEMENTARY

Over the past two decades, occupational conditions have emerged as likely risk factors for cardiovascular diseases.1 Shift work has been highlighted among these conditions.1,2 Although some studies do not support the association between shift work and cardiovascular morbidity and mortality,3,4 several studies convincingly indicate the existence of this causal relationship and even suggest the potential physiopathological mechanisms involved.1,5

Hypertension, obesity, diabetes mellitus type 2 and cardiac autonomic dysfunction have been suggested as important members of this not fully elucidated physiopathological model that, starting with desynchronisation of circadian rhythms, culminates in cardiovascular diseases.6,7 These intermediate disorders of the model are common findings among shift workers.5 (Figure 1)

 

 

Figure 1

 

For assessing cardiac autonomic dysfunction, the estimation of heart rate variability (HRV) using ECG is a good and non-invasive method.8-10 HRV has important sympathetic and parasympathetic components, and the reduction of the latter has been associated with a worse general health status and greater cardiovascular morbidity and mortality.11,12 Several studies have associated shift work with a reduced global HRV,2,8,13-15 indicating the existence of sympathetic preponderance and detrimental parasympathetic activity in this population.

This study was designed to evaluate the association between lifetime exposure to shift work and blood pressure, glucose levels, anthropometric variables, body composition and HRV.

Some relevant points of this study: the sample homogeneity (Brazilian, male, rotating shift, mine workers), multiple variables collected on the same sample and a principal component analysis (PCA) approach. PCA is a classical multivariate exploratory tool because it highlights the common variation between variables, allowing inferences about the potential biological meaning of associations between them without pre-establishing hypotheses on the cause–effect relationships.

We hypothesized that PCA might group in a same component the variables that relevantly behave in a similar biological way. With that, lifetime shiftwork exposure would be positively associated with the components that represent cardiovascular risk factors.

To substantiate our hypothesis we measured anthropometric [weight, body mass index (BMI), waist circumference (WC), neck circumference (NC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to height ratio (WHtR)], body composition [body fat mass (BFKg), body fat percentage (BF%), visceral fat area (VFA)], systolic (SBP) and diastolic blood pressure (DBP), glucose and heart rate variability variables [heart rate (HR), root mean square of the successive differences (RMSSD), high frequency (HF), low frequency (LF) and the LF/HF ratio] in a cross-sectional study with 438 adult Brazilian males who were older than 18 years and worked in shifts. Initially, a medical interview was performed to collect information on the use and dosage of medications, as well as to calculate the lifetime shift work. Next, anthropometric and body composition variables were measured. Subsequently, an ECG was performed for 3 min in the supine position. Finally, blood pressure was measured and blood sample was collected for the biochemical determination of glycaemia.

Our findings of PCA showed five principal components (PC) that accounted for 79.6% of the total variation of the data. For PC1, which accounted for 40.21% of the variance, 10 variables had loadings greater than the predefined cut-off point, indicating a strong positive association between weight, BMI, WC, NC, HC, WHR, WHtR, BFKg, BF% and VFA. In PC2, three variables (RMSSD, HF and LF) reached the cut-off point in the same direction of variation (positive loadings), corresponding to 14.95% of the total variation. Accounting for 10.02% of the total variation, only the pressure variables (SBP and DBP) were included in PC3. Contributing to 7.36% of the variation, PC4 was composed of positive loadings for HR and LF/HF. Finally, PC5 included the variables WHR and FG, accounting for 7.08% of the data variation. Because the analysis performed allows for naming the components according to what they appear to express from a biological point of view, the PCs were respectively named as: body obesity component; cardiac component of good regulation; blood pressure component; cardiac component of bad regulation and insulin resistance component (Figure 2).

The data from the linear univariate analysis of the association between lifetime shift work and each PC showed that component 2 (p=0.005) was negatively associated with lifetime shift work, while components 3 (p=0.023), 4 (p=0.017) and 5 (p=0.006) were positively associated with it. After age adjustment, the values of each PC were obtained for the different estimated lifetime shift work (5, 12, 18 and 24 years) for fixed ages (25, 35, 45 and 55 years old, respectively), which demonstrated that PC2 remained with a definitive negative association with lifetime shift work and PC3 with a definitive positive association.

 

 

Figure 2

 

Importance of the study:

First, using PCA we obtained five PCs which accounted for 79.6% of the total variation of the data, and grouped the measured variables into components of important biological value: body obesity component; cardiac component of good regulation; blood pressure component; cardiac component of bad regulation and insulin resistance component.

Second, after age adjustment, PC2 (RMSSD, HF and LF) remained with a definitive negative association with lifetime shift work and PC3 (SBP and DBP) with a definitive positive association, suggesting that shift work promotes unfavourable changes to autonomic cardiac control that are related to a decrease in parasympathetic modulation and an increase in blood pressure.

Therefore, the heart rate variability (RMSSD, HF and LF) and blood pressure should be persistently measured in shift workers in order to anticipate the diagnosis of health deterioration and ensure early intervention to minimize disease burden and improve quality of life in this population.

 

References:

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Acknowledgements: This work was supported by the Federal University of Ouro Preto (UFOP); the National Council for Scientific and Technological Development (CNPq); the Coordination for the Improvement of Higher Education Personnel (CAPES); and the Foundation for Research Support in Minas Gerais (FAPEMIG).

 

Contact:

Gabriela Guerra Leal Souza, PhD

Laboratory of Psychophysiology

Department of Biological Sciences

Institute of Biological and Exact Sciences

Federal University of Ouro Preto

Ouro Preto, Brazil

souzaggl@gmail.com

http://www.nupeb.ufop.br/lapf/

 

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