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Physical Work Capacity in Pregnant Women

  • Enrique de la Vega-Bustillos
  • Francisco Lopez-Millan
  • Alejandro Coronado Rios
  • Diana Lagarda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 824)

Abstract

Objective: Determine the Physical Capacity of Work (PCW) in pregnant women up to 35 years old working in the industrial manufacturing environment.

Justification: There is not, from a legal, labor or engineering point of view, a standard that indicates the amount of work a pregnant woman can do or the number of breaks she may need. Currently, Mexican legislation indicates that a pregnant woman must perform a “LIGHT” job, leaving this term open to various interpretations.

When we determine the PCW in pregnant women, we can assign them the workload they can develop depending on their age and gestation period, in other words, assign pregnant women to an adequate workstation.

Methodology:

  1. 1.

    Make a study of each of the women participating in the project to determine their health status.

     
  2. 2.

    Calculate the Energy Metabolic Expenditure (EME) of each of the stations assigned to pregnant women with the method proposed by Bernad and Joseph [1].

     
  3. 3.

    Perform a measurement of oxygen consumption in pregnant women with the VO2000® equipment while performing its activity in the assigned work station (Estimated maximum time: 60 min).

     

Description of the Study: Phase I: The study was developed with 17 pregnant women who were in different periods of gestation.

Phase II: The study was repeated with 5 of these 17 women who changed their gestation period of 1–2 or 2–3. Each woman performed a test for a minimum period of 30 min with VO2000® and determined the oxygen consumption and the corresponding Kcal/min. Total number of observations: 22.

Phase III: Age, period and weeks of gestation, previous births, and EME in Kcal/min were considered as input variables.

Results: With the data obtained, we determined the equation to predict the energy consumption in pregnant women by means of multiple linear regression analysis in the following way:

$$ \begin{aligned} & {\text{PCW}} = 8.0 + 0.06{\text{Age}}\;{-}\,0.00148{\text{Age}}^{2} {-}3.4{\text{MEE}} + 0.49{\text{MEE}}^{2} + 0.015{\text{MEE}}^{3} \\ & {\text{S}} = 0.61\quad {\text{R-Sq}}\left( {\text{adj}} \right) = 54.0\% \\ \end{aligned} $$

The model has a coefficient of determination 54%, which means that the variation can be explained by the variables considered only 54%.

Conclusions:

  1. 1.

    It is feasible to develop a method to determine the energy consumption in pregnant women working in a manufacturing environment.

     
  2. 2.

    We can now have a more confident idea of how we should assign pregnant women to workstations that are appropriate according to their pregnancy weeks.

     
  3. 3.

    Although the current model is “good”, more observations are needed to make it more robust under these considerations:

     

Keywords

Pregnant women Energy metabolic expenditure Physical Work Capacity 

References

  1. 1.
    Bernard TE, Joseph BS (1994) Estimation of metabolic rate using qualitative job descriptors. Am Ind Hyg Assoc J 55(11):1021–1029CrossRefGoogle Scholar
  2. 2.
    Ahlborg G Jr, Bodin L, Hogstedt C (1990) Heavy lifting during pregnancy – a hazard to the fetus? A prospective study. Int J Epidemiol 19:90–97CrossRefGoogle Scholar
  3. 3.
    Chamberlain BV (1993) Work in pregnancy. Am J Ind Med 23:559–575CrossRefGoogle Scholar
  4. 4.
    Marbury MC (1992) Relations of ergonomic Stressors to birth weight and gestational age. Scand J Work Environ Health 18:73–83CrossRefGoogle Scholar
  5. 5.
    Instituto Naciona de Estadistica, Geografia e Informatica 16 Sep 2017. [En línea] http://www3.inegi.org.mx/sistemas/cni/
  6. 6.
    Wren AO, Kidwell RE Jr, Kidwell LA (1996) Managing pregnancy in the workplace. Business horizons, November–December 1996CrossRefGoogle Scholar
  7. 7.
    Estrada Jairo (marzo 2000) Ergonomía 2da Edición, Editorial Universidad de AntioquiaGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Tecnológico Nacional de México/Instituto Tecnológico de HermosilloHermosilloMexico
  2. 2.Planta de Estampado y Ensamble Ford HermosilloHermosilloMexico

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