Download The Relationship Between Nonstandard Work Schedule and

The Relationship between Nonstandard
Work Schedule and Substance Use;
New Evidence From NLSY97
Mona Khadem Sameni
University of Wisconsin Milwaukee
November 2014
The Initial Thought
The shift working neighbor who
always smoked outside the
building…
Nonstandard Work Schedule
(Shiftwork)
 Other than: Regular Monday through Friday, nine to five schedule.
 U.S. Bureau of Labor Statistics (2004):
One-fifth of all employed Americans
Presser and Ward(2011):
One-third of all dual-earner couples with children
 NLSY 97:
• Regular evening shift
• Regular night shift
• Shift rotates
• Split shifts
• Irregular schedule or hours
Why should we care?
 Substance Use
Health hazards :
• Higher probability of accidents at work and outside work
(MacDonald, Wells et al. 1999)
• Higher risk of HIV (Gorman and Carroll 2000)
• Higher probability of major depression (Libby, Orton et al. 2005).
Significant economic health costs :
• Specialty treatments
• Hospitals and emergency departments
• Homicide and insurance administration participation
• Hospitalization and premature mortality.
Why should we care? (Continued)
Efficiency and social costs
• Lower productivity of the workforce
• Higher crime rates such as drunk driving or drug
possession and sale
• Dependence on various pension types
Potential Mechanisms Affecting Health
 Psychosocial mechanisms :
• Related to family and social activities
(Wirtz and Nachreiner 2010); (Drake, Roehrs et al. 2004)
(Llena-Nozal, Lindeboom et al. 2004)
 Physiological mechanisms :
• Circadian rhythms
• Sleep patterns closely related to melatonin and growth
hormone levels.
(Davis, Mirick et al. 2012); (Arendt 2010); (Srivastava 2010)
Previous Literature
 Job conditions  Not a significant effect on drug use (Mensch and Kandel
1988)
 Working night shifts + more than eight hours/ rotating shift  Higher amount
of alcohol use (Trinkoff and Storr 1998)
 Nonstandard schedules Worse health conditions (Esp for men) (Ulker
2006)
 Being a shift worker  Higher odds of drinking alcohol in short-term (Dorrian
and Skinner 2012)
Contributions to The Literature
 First to use a US nationally representative longitudinal
survey in this field.
 First to investigate five separate substances.
 First to use survival analysis that corrects for frailty.
Is Nonstandard Work Schedule Always
“Bad”?
• More free time (during the day)
• Saving existing jobs (ILO 2004)
• Helping with school
• Fewer unwanted family interactions
• Less tension and more relaxed pace
• Accommodating “night owls”.(Finn 1981)
Research Question
 Do shift workers indicate higher hazard ratios for the
onset of substance use compared to regular day
workers?
 People who held non self-employed jobs within the past
year.
Data
 U.S. National Longitudinal Survey of Youth, NLSY 97.
 Rounds 1-15 : 1997-2011
Five different categories :
• Employed not shiftwork
• Employed shiftwork
• Unemployed
• Out of the labor force
• Military
 Reference group : Employed not shiftwork
Data Continued
 Substances :
• Alcohol
• Excessive use of alcohol (Binge Drinking)
• Cigarettes
• Marijuana
• Cocaine
Methodology
 Duration framework using Cox (1972) Proportional Hazards Model.
 Why duration model?
Impact of being in nonstandard work schedule on the length of time
(length of spell) it takes to start using any type of previously mentioned
substances.
 Results of Cox (1972) : The probability of starting to use any
substance given that the individual has not done so yet.
 Model : 𝝀𝟎 (t) exp (β’x)
• Regular control variables
The Importance of Fixed Effects
Estimation Besides Cox Model
 Previous work in this field suffer from selection bias
 Fixed effects : As if there were “before and after” shift
work.
 Identical to DID estimation.
 Benefit of longitudinal data.
Survival Plots
Alcohol
Binge Drinking
Cigarettes
Marijuana
Cocaine
Substance Use at Different Ages
Drinkers at Different Ages
Binge Drinkers at Different Ages
Smokers At Different Ages
Marijuana At Different Ages Cocaine At Different Ages
Regression Results
Pooled
OLS
Fixed
Effects
Random
Effects
-0.012
(3.09)**
Cox without
Frailty (no
hazard rate)
-0.090
(3.75)**
Cox with frailty
correction(no
hazard rate)
-0.066
(2.75)**
Alcohol
-0.003
(0.85)
-0.019
(4.39)**
Binge Drinking
-0.001
(2.00)*
-0.009
(2.01)*
-0.009
(2.13)*
-0.054
(2.47)*
-0.057
(2.61)**
Cigarettes
-0.003
(0.98)
-0.003
(0.88)
-0.004
(1.35)
-0.068
(2.89)**
-0.105
(4.47)**
marijuana
0.004
(1.19)
-0.005
(1.67)
-0.002
(0.86)
-0.051
(2.33)*
-0.071
(3.25)**
cocaine
0.01
(5.35)**
0.004
(1.85)
0.006
(3.30)**
-0.015
(0.68)
-0.035
(1.58)
Type of
Substance Use
Ruling out Reverse Causality!
 Shift workers use more substance or substance users do more
shift work?
 Negative coefficients  Less concern about upward bias.
 Pooled OLS gives smaller negative or positive coefficients 
Upward bias in previous literature using cross sectional data
Conclusion
 Nonstandard schedules decrease the odds of the onset
of drinking and binge drinking.
 Marijuana and cigarettes : Mixed results
 Cocaine: weakest evidence and even slightly on the
opposite direction.
 Social aspect of work schedule Affecting teenagers
and young adults more.
 Working at odd hours keeps them away from their circle
of friends and family.
Limitations and Future Work
 Not every nonstandard schedule has the same effect
(Data limitation)
 Using a similar sample of adults seems appropriate.
 Application of exogenous variation methods.