Trends%20in%20Work%20Place%20Injury%20and%20Consequent%20Absence%20from%20Work%20in%20the%20County%20of%20G - PowerPoint PPT Presentation

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Trends%20in%20Work%20Place%20Injury%20and%20Consequent%20Absence%20from%20Work%20in%20the%20County%20of%20G

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Trends in Work Place Injury and Consequent Absence from Work in the County of G vleborg, Sweden Leah Okenwa Emegwa O.D, MPH, PhD 2014-06-24 – PowerPoint PPT presentation

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Title: Trends%20in%20Work%20Place%20Injury%20and%20Consequent%20Absence%20from%20Work%20in%20the%20County%20of%20G


1
  • Trends in Work Place Injury and Consequent
    Absence from Work in the County of Gävleborg,
    Sweden

Leah Okenwa Emegwa O.D, MPH, PhD 2014-06-24
2
  • The University of Gävle

3
Background
  • Work place injuries contribute to the global
    burden of disease and injuries
  • Roughly a million workers injured and a thousand
    die per day
  • One year incidence is about 3.2
  • Known risk factors include age, gender,
    occupation etc.
  • Different direction of association in different
    contexts

4
  • Causes of work related injury include
  • Falls, Loss of control
  • Movement with or without load
  • Violence, Electricity/fire/explosion
  • Leakage/overflow
  • Slip/snapping/splitting/breaking of an object

5
  • About 317 million workers were injured in
    accidents at work that resulted in absence from
    work of four days or more
  • Equivalent to roughly 850,000 injuries per day
  • (Global Estimates)

6
  • Sick leave good for reccuperation
  • Grave consequences if too long or too short
  • Examples for too long
  • Negative psychosocial health outcomes
  • Loss of job etc
  • Examples too short (sickness presence)
  • Non full recovery
  • Risk of reccurrent short sick leave
  • Loss/waste of economic resources
  • Lower productivity

7
Work related injury and illness pattern, Sweden
Work related injury men Work related illnesses
men
Work related injury women Work related illnesses
women men
Source Statistics Sweden
8
  • Rationale for study
  • Most studies address certain injuries types in
    certain industrial sectors
  • Others present aggregates
  • Same for sick leave duration
  • Need for studies at county level due to
  • -i.Health care administered at county level)
  • -ii. Companies pay sickness benefits first two
    weeks

9
Aim
  • To explore trends in workplace injuries and
    associated risk factors in the county of
    Gävleborg, Sweden
  • The study also aims to investigate sick leave
    duration and its determinants

10
Gävleborg, Sweden.
  • Gävleborg, Sweden
  • Centrally located by the east coast
  • 280 000 inhabitants living on almost 20 000 km2
  • Three-quarter woodlands
  • Lakes, hills and mountains

11
Method
  • Design
  • Based on Register kept by the Swedish National
    Working Environment Agency
  • Includes all cases of occupational injuries
    requiring at least one day of sick leave reported
    to the Swedish social security board

12
  • For the present study
  • All cases of non fatal occupational accident
    between 2007-2012
  • Total 5291cases

13
  • Measures
  • Dependent Variables
  • Injury Cause
  • Sick leave
  • lt2weeks
  • gt2weeks

14
  • Independent Variables
  • -age
  • -gender
  • -occupational sector
  • -Employment status

15
  • Data analysis
  • SPSS
  • Descriptive analysis
  • Logistics regressions
  • Significance level plt0.05
  • 95 confidence interval.

16
  • Ethical consideration
  • Ethical approval granted by institutional review
    board for the region.

17
  • Results
  • Loss of controll
  • Proportion decreases with age (49 vs. 23)
  • More men
  • Agriculture (43.7) and mining (55.6)
  • Student/trainees (49.4) and self employed and
    (36)
  • Adjusted odds ratio (significant)
  • 1.8 odds for lt20yrs
  • 1.5 for 20-29yrs
  • 2.5 odds for students/trainees

18
  • Fall
  • Increases with age (12.9 vs. 41.4)
  • More women (35.1 vs. 22.4)
  • More than one third of workers from Specific
    sectors e.g. electricity/gas, infomation
    communication, transport, real estate, health
    and education.
  • Adjusted Odds Ratio
  • Increasing OR with age
  • Sex remained a predictor (more women)
  • 2times risk in real estate sector
  • 1.4 times risk for permanent workers

19
  • Movement involving load
  • Significantly more among
  • Age 40-49yrs (10.3)
  • Women (13.5)
  • Healthcare sector (23.3)
  • Adjusted odds
  • Risk increases with age up to 40-49 yrs
    (1.6times)
  • Higher risk remained for women
  • 4.6 times risk for workers in health care

20
  • Slip/snapping/splitting/breaking of an object
  • More men (7.6)
  • Mostly in construction (11.5)
  • Mostly among self employed (22)
  • Adjusted OR
  • Greatest risk for 30-39yr (1.6times)
  • 2.8times risk for men
  • Significance remained for self employed

21
  • Interpersonal Violence
  • Highest for age 20-29yrs (15.8) then reduces
    with age
  • More men (13.6 vs. 11)
  • Most common in Financial sector (50) and
    Manufacturing (19.5)
  • Adjusted OR
  • Risk 1.6 times for 20-29 yrs
  • 3.5 times risk for manufacturing
  • 15.8 times for financial sector

22
  • Movement not involving load
  • Significant only for age
  • Remains after adjusting for other factors

23
  • Electricity/fire/explosion
  • Increasing proportions among younger workers
  • More men
  • Construction sector (3.1)
  • Adjusted odds
  • 10.8 times risk for men

24
  • Leakage/Overflow
  • Higher among men (2)
  • More in mining sector (11.1)
  • Adjusted OR
  • Significance disappears

25
  • Sick leave longer than two weeks
  • Increases with age
  • About 2 times risk for injuries resulting from
    fall, slip/snapp/splitting/breaking of object and
    violence
  • Sick leave longer than two weeks less likely
    among workers in Healthcare and Manufacturing
    sectors
  • More than twice likelihood (2.2 times) among self
    employed

26
  • Discussion/Conclussions
  • Loss of controll associated with age and
    inexperience (students/trainee)
  • Risk for fall with increasing age a time for
    setting age limit for certain task?
  • Movement while carring a load healthsector and
    women
  • Interpersonal violence (16 times risk for
    financial 3.5 manufacturing)
  • Lenght of sick leave- an indication of severity
    and/or other factors
  • Quick return to work and Sickness presenteeism
    following injury how beneficial in the long run?
    (lower reporting of injuries requiring sick
    leave)

27
Iceberg of Presenteeism
28
  • Reccomendations
  • More industry specific safety policies and
    monitoring
  • Gender consideration in prevention and
    rehabilitation
  • Closer monitoring of self employed to minimise
    injury risks
  • Calls to build resilience against presenteeism in
    organisations (Health and Wellbeing
    Questionnaire first step)
  • The need for continous emphasis on training,
    monitoring and evaluation of existing policies

29
  • Strengths and Weaknesses
  • Strengths
  • Reliable database shown by level of precision
  • Weaknesses
  • Few variables
  • Not able to compare non injured workers vs.
    Injured

30
  • Implications for Future Research/Policy/Innovatio
    n
  • The dynamics involved and factors responsible for
    shorter sick leave duration in health and
    manufacturing sectors. i.e. severity vs. Sickness
    presenteeism
  • Opportunities for Bussiness innovations-
    development of more safety products (movement
    under load)
  • Review of existing policies, training programs
    and monitoring systems

31
  • Tack! (Thank You!)
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