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Garment Workers’ Health and Nutrition
Status, and Food Provision in Factories
A Study from Selected Enterprises in Cambodia
©ILO/Piotr Zaporowski
May 2016
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Acronyms and Abbreviations
AFD
ARC
BFC
BMI
CDHS
cm
CSPro
DID
FANTA
FAO
FCS
FDC
FIAS
g/dL
GMAC
Hb
IDDS
ILCC
ILO
Kcal
kg
KHR
M/M
M&E
MOLVT
MUAC
SD
SE
WASH
WB
WHO
USAID
USD
WDDS
μg
Agence Française de Développement (French Development Agency)
Angkor Research and Consulting
Better Factories Cambodia
Body mass index
Cambodia Demographic and Health Survey
Centimetre
Census and Survey Processing System
Difference-in-difference
Food and Nutrition Technical Assistance project (funded by USAID)
Food and Agriculture Organization
Food Consumption Score
Fixed duration contract
Food Insecurity Access Scale
gram per decilitre (measurement of haemoglobin levels)
Garment Manufacturers Association in Cambodia
Haemoglobin
Individual dietary diversity score
Industrial Laboratory Center of Cambodia
International Labour Organization
Kilocalorie
Kilogram
Khmer riel (4,000 KHR = 1.00 USD)
Mass over mass (unit of calculation)
Monitoring and evaluation
Ministry of Labour and Vocational Training
Mid-upper arm circumference
Standard deviation
Standard error
Water, sanitation and hygiene
World Bank
World Health Organization
United States Agency for International Development
United States dollar
Women’s Dietary Diversity Score
microgram (1,000,000μg = 1 gram)
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Table of Contents
Acronyms and Abbreviations ............................................................................................................................ 2
Table of Contents .............................................................................................................................................. 3
Table of Tables................................................................................................................................................... 4
Table of Figures ................................................................................................................................................. 4
1.
Introduction ............................................................................................................................................... 5
2.
Summary.................................................................................................................................................... 7
General characteristics .............................................................................................................................. 7
Health indicators ....................................................................................................................................... 7
Nutritional characteristics ......................................................................................................................... 7
Food provision ........................................................................................................................................... 8
Methodology ............................................................................................................................................. 8
Highlighted findings ................................................................................................................................... 8
Discussion .................................................................................................................................................. 9
Lessons learned ......................................................................................................................................... 9
3.
Participating Factory Profile .................................................................................................................... 10
4.
Garment Worker Profile .......................................................................................................................... 10
4.1 General worker characteristics ............................................................................................................. 10
4.2 Health characteristics ............................................................................................................................ 12
4.2.1 Height, weight and BMI .................................................................................................................. 12
4.2.2 MUAC (pregnant females) .............................................................................................................. 13
4.2.3 Anaemia .......................................................................................................................................... 13
4.2.4 Sickness and fainting/dizziness ...................................................................................................... 14
4.3 Nutritional characteristics ..................................................................................................................... 15
4.3.1 Typical daily diet ............................................................................................................................. 15
4.3.2 Food consumption .......................................................................................................................... 16
4.3.3 Food security .................................................................................................................................. 17
5.
Food Provision ......................................................................................................................................... 18
5.1 Food provision - different approaches .................................................................................................. 19
5.1.1 Nutritional content ......................................................................................................................... 19
5.2 Participation in food provision .............................................................................................................. 20
5.3 Perceptions of food provision ............................................................................................................... 20
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
6.
Methodology ........................................................................................................................................... 21
6.1 Data collection timeline......................................................................................................................... 22
6.2 Instrument and indicators ..................................................................................................................... 22
6.2.1 Anthropometric data and blood testing......................................................................................... 22
6.3 Data management (entry and analysis) ................................................................................................ 22
6.4 Limitations ............................................................................................................................................. 23
7.
Highlights of Findings .............................................................................................................................. 24
7.1 Food consumption, food security and health ....................................................................................... 25
8.
Discussion and Lessons Learned.............................................................................................................. 26
8.1 Analysis and recommendations ............................................................................................................ 26
8.2 Lessons learned in food provision implementation .............................................................................. 28
9.
References ............................................................................................................................................... 32
Annex 1: Significant results produced by DID analysis .................................................................................... 34
Table of Tables
Table 1 Garment workers' general characteristics .......................................................................................... 11
Table 2 BMI categories (following BMI range for Asia) ................................................................................... 13
Table 3 Prevalence of anaemia among garment factory workers (at third data collection) .......................... 14
Table 4 FCS categories ..................................................................................................................................... 17
Table 8 Caloric content of food provisions, by type of food provision ........................................................... 19
Table 9 Perceptions of food provision as reported by treatment factory workers, from the second to the
third survey (Dec. 2014 – June 2015). ............................................................................................................. 21
Table of Figures
Figure 1 Daily dietary diversity of all non-pregnant female workers in the 24 hours before the final survey
(2015) .............................................................................................................................................................. 16
Figure 2 Weekly food consumption by FCS categories, for all workers at the final survey (2015) ................. 17
Figure 3 Food insecurity categories among all workers .................................................................................. 18
Figure 6 A model of difference-in-difference analysis (Note: s=1 is the control group at the start and s=2 is
the treatment group at the start. Source: Wikipedia. Used under Creative Commons license.) ................... 23
Figure 7 Proportion of workers experiencing FIAS conditions in the month before the final survey ............ 25
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
1. Introduction
The garment industry is the single largest formal employer in Cambodia, providing over 600,000 jobs in
more than 500 export factories, representing roughly a 5.8 billion USD worth industry and around 80% of
Cambodian exports (ILO 2015a; ILO 2015b). According to Better Factories Cambodia estimates, the garment
and footwear sector provide support to approximately 2 million people in Cambodia. Much of the appeal of
this industry for investors is due to the low wage structure, and the availability of a young labour force,
among other competitive advantages; Cambodian garment workers make less than their counterparts in
neighbouring countries such as Vietnam and Indonesia (ILO 2015a; ILO 2015b). Most of the workers in this
industry – around 80% – are female.
A common concern is workers’ health and general welfare, especially in light of the mass faintings that
continue to occur in factories. In 2012, the Ministry of Labour and Vocational Training (MOLVT) reported
fainting of 1,686 workers in more than 20 factories. In 2015, the same ministry reported 1,806 faintings in
32 factories. Cited contributing factors to worker fainting episodes included the smell of paint and
pesticides inside the premises, poor health and hygiene, and fatigue. Despite Cambodia’s economic growth,
its garment sector is among the least productive in the region. There are many discussions about the
factors behind this, including theories about the correlation between workers’ food intake, health and
welfare, but large-scale studies on these phenomena are rare. Despite speculation, there has been no
substantial examination of workers’ health and nutritional status, including food consumption and food
security.
In an attempt to improve the understanding of some factors that influence the Cambodian garment sector
and affect workers’ wellbeing, the Better Factories Cambodia (BFC) program of the International Labour
Organization (ILO) funded a study in 2012 on the perceptions of garment factory owners towards workers’
nutritional status and the provision of canteen services (BFC 2012b)1. Subsequent research has been
undertaken following the 2012 study. This publication presents the findings of research commissioned in
2013 about workers’ physical health status, food consumption and food security in factories with and
without food provision programs. The study was realised by BFC with funding from the US Department of
Labor and in partnership with Agence Française de Développement (French Development Agency; AFD).
This research commenced in early 2014, and was conducted by Angkor Research. The study encompassed
eight factories employing over 10,000 workers, of which 3,302 were randomly selected for the study. Four
factories provided food to workers (known as the ‘treatment’ factories) and four factories did not provide
any food (the ‘control’ factories). The workers selected for the first survey were tracked for more than one
year and underwent three rounds of individual interviews from April 2014 to June 2015. The first round of
data collection occurred shortly before the start of food provision in treatment factories. The second and
third interviews occurred six months and 12 months after the start of food provision. In order to
complement data from the workers’ survey and extract lessons learned from an implementation point of
view, BFC independently carried out interviews with managers in factories with food provision initiatives.
1
Supported by ILO, the Garment Manufacturers Association in Cambodia (GMAC), Hagar Catering, and conducted by
BDLINK Cambodia. It must be noted that this research was not conducted in response to mass faintings in factories.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
A number of limitations of this study have to be acknowledged. First, the factories were not randomly
selected. Because participation in the survey and provision of food was voluntary, the study findings are
not representative of the sector as a whole. Any attempt at generalisation should be considered carefully.
Second, the type of food offered to workers was chosen and provided by the employer, sometimes in
collaboration with the main buyer, and differed among the treatment factories; factories provided either a
hot lunch, an afternoon snack, or a pastry and bottle of water. The caloric and nutritional content of the
different interventions differed substantially and it can therefore be expected that the effects on physical
health, food consumption and security vary.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
2. Summary
General characteristics





Female workers account for 82.3% of the workforce.
The average worker completed six years of school.
More than 55% of all workers are married, of which 71.7% have on average 1-2 children.
Sixty-five percent of parents live with their children. Another 39.4% of workers are still single.
However, almost all workers (95.1%) live with another person, typically a worker lives with three
other people (mostly with (extended) family or spouse).
The average garment worker had more than 5 years (5.2 years) of work experience in the garment
sector, including three years in their current factory.
Health indicators





The average garment worker in 2015 was around 52kg in weight and 155cm tall, with a body mass
index (BMI) of 21, which is well within the ‘normal’ range.
Around two-thirds of all workers (61.2%) are within the normal body mass index (BMI) range (18.522.99kg/m2). Almost a quarter of workers (24.0%) are considered either overweight (19.4%) or
obese (4.6%), and at increased or high risk of disease. Twelve percent of workers are slightly
underweight, while 2.9% of workers are either moderately or severely underweight, which is
similar to people in the overall population.
Nearly all pregnant women (93.6%) were considered to have a normal mid-upper arm
circumference (MUAC).
Eighteen percent of non-pregnant garment workers had moderate or severe anaemia, compared to
around 6% of non-pregnant women in the general population. One-third (33.8%) of male garment
workers were anaemic. Pregnant workers had the highest rates of anaemia in 2015. Nearly twothirds (61.4%) of pregnant women were classified as anaemic, of which nearly one-third (31.1%)
having moderate anaemia, which is around eight percentage points higher than pregnant women
in the overall population.
In 2015, one-quarter of workers (24.8%) reported taking time off for illness in the month before the
final survey, taking an average of two days off of work when sick. Another 17.5% reported feeling
sick for an average of two days, but did not take any time off. Nearly half (46.5%) of all respondents
felt dizzy, light-headed, tired, or had cold hands/feet (signs of poor nutrition or anaemia) in the
same time period, but less than one percent of workers fainted at work.
Nutritional characteristics


The typical daily diet of a non-pregnant female garment worker consisted of nine different food
groups in the last day (spices/condiments, cereals (rice), oils and fats, dark leafy green vegetables,
flesh meat, fish, sweets, other vegetables, fruits). Dairy products and foods rich in vitamin A are
largely missing.
Workers’ food consumption shows an acceptable amount of dietary diversity. Food consumption
score (FCS) analysis shows that the average worker consumes food from six out of eight food
groups. The basic weekly diet for workers with the lowest FCS was mostly composed of staples
(rice, bread), animal proteins (meat/fish), oil and some vegetables.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
One-quarter of workers experienced one or more food insecurity access scale (FIAS) conditions.
The most common FIAS conditions were worrying about having sufficient food and not being able
to eat preferred foods.
Food provision


Food was provided to workers on all working days in four different factories. The types of food
provided differed amongst factories. One factory provided a hot lunch every day, one factory
provided a mid-afternoon snack (fried noodles or a dessert), and two factories provided a pastry
and a bottle of water in the morning.
All factories participated in this study and provided food on a voluntary basis, sometimes with the
cooperation of their brand partners.
Methodology





The study utilised a quasi-experimental research design, based on two components: a longitudinal
sampling and a selection of treatment and control groups. The same workers were interviewed
during all three surveys.
The first data collection point was in May 2014 (the food intervention started in treatment factories
in June 2014). The second survey was in December 2014, and the final one in June 2015, 13 months
after the food interventions started in the treatment factories.
The quantitative survey included self-reported data on indicators of various worker characteristics.
The same survey was conducted across all three data collection points. Anthropometric data was
collected to measure height and weight (to calculate BMI), mid-upper arm circumference (MUAC),
and bilateral oedema. Haemoglobin levels were measured to assess anaemia.
To understand the effects of food provision on the treatment factory workers, the key indicators
were analysed using a difference-in-difference (DID) design across all three survey rounds.
A number of limitations have to be taken into account. Most notably, the participating factories
were not randomly selected, and there may be differences between groups of factories beyond
what has been examined. Further limitations include the self-reporting of some data2 and a lack of
micronutrient analysis.
Highlighted findings


Workers in the study had average FCS scores (measuring weekly food consumption and dietary
diversity) of 57.5 in 2015, up from the first survey scores of 55.7, with a minimum FCS of 26.
From the first to the second survey, treatment factory workers showed significantly higher FCS and
FIAS scores than control factory workers. Also, from the first to the second survey, treatment
factory workers became significantly more food secure than control workers.
2
Thus, respondents may have over-reported or under-reported their status on indicators such as debts, savings,
monthly food or non-food expenditures, their food consumption occurrences and/or frequencies during the previous
day, week or month, for a variety of reasons (forgetfulness, loss of face, hope of additional support, fear of
repercussion, etc.). Anthropometric and factory-provided data attempt to control for some of these inaccuracies, by
providing unbiased metrics on health and productivity indicators.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories


Workers in treatment factories who always ate the food provided by factories had more dietary
diversity than workers who occasionally or never ate the food provisions (FCS scores of 6.5 and 6.3,
respectively). However, this did not translate into significant increases in food consumption or food
security (FIAS) over the total duration of the study.
The treatment factory that provided workers with a full meal had no workers with severe food
insecurity by the time of the third survey, unlike all other treatment and control factories.
Discussion
The findings point to some important issues for further discussion and consideration, as well as areas
where further research would be highly beneficial. When initiating or continuing work on nutrition and
health programs, the following points can be considered:
 In designing food interventions, it is important to ensure any food provision program provides
food that is nutritious and culturally appropriate, as these variables can affect the uptake of the
food and health outcomes. Further research would be beneficial to investigate the impacts of
food interventions with different nutritional contents.
 Working in partnerships to share good practices and increase the reach of food provision
initiatives would be important for expanding the scope and impacts of food provision
programs.
 Training on nutrition, dietary diversity and hygiene could be beneficial to increase beneficiaries’
knowledge and change behaviours with regards to a healthier lifestyle.
 Further research into the prevalent causes of anaemia in target populations would be very
important to understand this complex problem and to identify effective strategies to tackle it.
Depending on the identified causes, specific strategies to reduce anaemia would be required.
 In populations with overweight and obesity issues, exercise classes may be considered to help
improve health status.
Lessons learned3
When designing and implementing food provision programs, it is important to consider the following:




Ensure food is well accepted by the target group and nutritionally rich. This can support the uptake
of food provision, as well as the health benefits associated with it.
Establish communication channels for worker feedback, to promote a review of the food provision
program and workers’ participation.
Ensure hygienic food preparation, as this is fundamental to support the health benefits of food
provision.
Consider the logistics of food provision and distribution, and establish canteen rules to maximise
efficiency. These include the choice of an appropriate location, investments in proper equipment,
serving in shifts to ensure all beneficiaries have sufficient time to receive and eat the food, and
effective planning of food purchase, preparation and clean-up.
3
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
3. Participating Factory Profile
In total, workers from eight different factories participated in the three survey rounds. The factory profiles
are briefly presented here. These factory characteristics were not included in the analysis, but may serve as
input for further research, as workers’ health and wellbeing is expected to be correlated with a variety of
variables.
All eight factories have produced garments in Cambodia for several years. They produce for international
buying houses and reputation-sensitive brands. The size of the factories varied from over 450 workers to
around 2,400 workers. Five factories paid their workers based on the basic wage system, and three
factories paid workers based on a piece rate system. The BFC compliance rates for these factories varied
from 81% to 98% compliant. Almost all factories had incentives and good practices that went beyond the
requirements of the labour law. There was a difference in average take-home pay between the treatment
and control factories based on data from the Ministry of Commerce. Generally speaking, all workers in the
surveyed factories had contracts, with the majority working on fixed duration contracts (FDCs).
4. Garment Worker Profile
This first section on the findings of the project describes a number of characteristics of the surveyed
workers, including the health and nutritional characteristics. Results have been weighted based on the
probability of respondent selection among all eligible workers in each participating factory, and are
representative of the eligible worker population of all target treatment and control factories4.
4.1 General worker characteristics
Female workers make up the large majority of garment workers in target factories, accounting for 82.3% of
eligible workers in all factories. This is within the same range of female workers for the sector overall,
based on BFC data (80-85% female in 2015). Garment factory workers constitute a rather young
population; the average worker is 28 years old.
Nearly all (94.9%) workers have some formal education. Among workers with some formal schooling, the
average worker completed six years of school; i.e., they completed primary education. Generally, more
than half of all workers are married (55.6%), while another 39.4% are still single. A small number of workers
are widowed (2.9%) or divorced (2.0%). Around three-quarters (71.7%) of non-single factory workers have
children. The average parent has 1-2 children (mean 1.7; median 1)5. Among these mothers/fathers, 65.4%
currently live with their children6.
4
These findings are based on data collected during the third data collection period in June 2015.
5
Treatment factory parents have significantly more children than control factory parents, and are also significantly
more likely to be pregnant at the third data collection point.
6
81.2% of parents at treatment factories live with their children, compared to only 31.8% of parents that work at
control factories. This difference is statistically significant (p<0.05).
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Nearly all of the garment factory workers (95.1%) live with another person. The typical worker lives with an
average of three other people. Among workers that live with another person, most (63.4%) live with
extended family members, and almost half (49.7%) live with their spouse. Around one in ten workers live
with their friends/colleagues.
The average garment worker in the survey worked in the garment sector for over five years (5.2 years),
including three years in their current factory, although some workers have worked in garment factories for
up to 17 years. Most workers had worked in two different factories at the time of the final survey.
Table 1 Garment workers' general characteristics
Variable
Sex
Male
Female
Age (years)
Mean
Median
Province of origin (5 most represented)
Kampong Speu
Prey Veng
Takeo
Kandal
Kampong Cham
Province of residence
Phnom Penh
Kampong Speu
Kandal
Takeo
Number of years lived in this province
Mean
Median
Education
Attended school
Highest grade completed (Mean)
Highest grade completed (Median)
Marital status and children
Married
Single
Widow
Divorced
Living together (not married)
Has children
Number of children (Mean)
Number of children (Median)
Pregnant (female respondents only)
Total
17.7%
82.3%
28.0
27
36.7%
11.6%
8.8%
8.7%
8.6%
64.2%
26.0%
9.5%
0.3%
13.4
7
94.9%
6.4
6
55.6%
39.4%
2.9%
2.0%
0.1%
71.7%
1.7
1
6.6%
11
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Variable
Total
Living with… (multiple answers)
Alone
4.9%
Other family members
63.4%
Spouse
49.7%
Children
28.9%
Friends
6.2%
Work colleagues
2.8%
Number of people accommodation is shared with
Mean
2.9
Median
3
4.2 Health characteristics
As part of data collection, a range of measurements were taken to understand workers’ current health
status. These indicators were: 1) sex, and pregnancy status of females; 2) height and weight, which were
used to calculate body mass index (BMI) as a measure of overall health and nutritional status; 3) mid-upper
arm circumference (MUAC), another test of nutritional status (especially in pregnant women); 4)
haemoglobin levels, to test for anaemia; and, 5) bilateral oedema, a test of severe malnutrition.
4.2.1 Height, weight and BMI
The average worker in 2015 was around 52kg in weight and 155cm tall, with a BMI of 21 (average 21.3;
median 20.8). This BMI is well within the ‘normal’ range for Asian populations, as developed by the World
Health Organization (WHO), and was consistent across male, female and pregnant female workers. This
BMI is also similar to the average BMI for Cambodian women found in the Cambodia Demographic and
Health Survey (CDHS) 2014 (22.0; excluding pregnant women). However, individual garment workers
display a wide range of BMI values; with a minimum value in the third survey of 13.3, indicating an
individual who is severely thin, and a maximum value of 35.3, indicating someone with severe obesity.
Classifying factory workers into BMI categories, around two-thirds of all workers (61.2%) are within the
normal BMI range (18.5-22.99kg/m2; Table 2). A further quarter (24.0%) of workers are considered either
overweight (19.4%) or obese (4.6%), and at increased or high risk of disease. Around one in seven workers
(14.9%) are thin or underweight. Most of these are slightly underweight (12.0%), while 2.9% of workers are
either moderately or severely underweight.
Female garment workers in this study have similar underweight levels compared to women in the overall
population; 14.3%, compared to 14.0% among all women (CDHS 2014). Regarding overweight and obesity,
because of differences in the methodology of the CDHS (which used the international BMI, rather than the
specific calculations for Asian populations), the results could not be compared.
12
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Table 2 BMI categories (following BMI range for Asia)
Variable
BMI Categories
Severe thinness
Moderate thinness
Mild thinness
Acceptable
Increased risk
High risk
Total
All workers
0.5%
2.4%
12.0%
61.2%
19.4%
4.6%
100%
Male
0.4%
2.7%
14.1%
63.9%
16.6%
2.5%
100%
Female non-pregnant
0.5%
2.3%
11.5%
60.5%
20.1%
5.1%
100%
4.2.2 MUAC (pregnant females)
Although BMI is a common method for assessing malnutrition in adults, the measurement of mid-upper
arm circumference (MUAC) is another tool that can be used to measure acute malnutrition, especially for
pregnant women and those with bilateral oedema or swelling, where body weight and BMI are affected by
foetal weight or fluid retention. There are many different classification systems for MUAC measurements in
adults, none of which is clearly recommended over the others (HTP 2011). For purposes of this research, it
was decided to use the WHO 1995 classification system for adult MUAC.
The average MUAC measurement for factory workers is 25.7 cm, with little variation between the average
and median. This is well above the cut-off for acute malnutrition (23.1cm in men and 22.4cm in women).
Among pregnant females, the average MUAC measurement was 24.6cm in 2015. Nearly all pregnant
females (93.6%) in participating factories were considered to have a normal MUAC measurement. Only
6.4% had MUAC below 21.0cm, signalling nutritional risk.
4.2.3 Anaemia
Anaemia is characterised by a low level of haemoglobin in the blood. Haemoglobin transports oxygen from
the lungs to other tissues and organs in the body. Anaemia can result from a nutritional deficiency of iron,
folate, vitamin B12, or other nutrients. This type of anaemia is commonly referred to as iron-deficiency
anaemia and is the most widespread form of malnutrition in the world (CDHS 2014). In these cases, dietary
changes (in combination with food supplements) usually have good results in improving iron levels.
However, anaemia can also be the result of haemorrhage, chronic diseases, malaria, or parasitic infection,
in which case the absorption of iron by the body is more limited. Genetic disorders such as haemoglobin E
trait, beta-thalassemia, and alpha-thalassemia permanently affect the haemoglobin (red blood cell)
production (CDHS 2014). For people with these disorders, increased iron or micronutrient intake will not
substantially improve haemoglobin levels. Some of these genetic disorders may be more prevalent in the
Southeast Asian region, but more research is needed to draw conclusions on the different causes of
anaemia in the region and Cambodia in particular.
In 2015, around half (55.8%) of all workers in the study were non-anaemic, with average haemoglobin
levels of 12.1 g/dL. Average haemoglobin levels are highest among the male garment workers (13.4 g/dL),
and decrease for females (11.9 g/dL) and pregnant females (10.6 g/dL), following standard physiology.
Pregnant workers had the highest rates of anaemia in 2015, with nearly two-thirds (61.4%) of pregnant
13
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
workers classified as anaemic and with nearly one-third (31.1%) having moderate anaemia. Nearly half
(45.4%) of non-pregnant females were anaemic, compared to only about one-third (33.8%) of males
surveyed.
These rates of anaemia in the garment worker population are considerable (Table 3). However, prevalence
among non-pregnant females in generally in line with CDHS 2014, where 43.8% of non-pregnant
Cambodian women of reproductive age (15-49 years old) were reported as anaemic. It should be noted
that there is about a ten percentage point variation between mild anaemia and moderate anaemia rates
for surveyed garment workers compared to the overall population. Only around 6% of non-pregnant
women in the general population have moderate or severe anaemia, compared with 18% of non-pregnant
garment workers. The anaemia rate of pregnant garment workers in the survey is higher than pregnant
women in the overall population (53.2% in CDHS 2014). Nearly one-third (31.1%) of pregnant workers had
moderate anaemia in 2015, compared to 22.8% of pregnant women in the overall population. Thus,
moderate and severe forms of anaemia may be more common among women in the garment sector than
in the overall Cambodian population.
Table 3 Prevalence of anaemia among garment factory workers (at third data collection)
Variable
Third survey, June 2015
All workers
Non-anaemic
Mild anaemia
Moderate anaemia
Severe anaemia
Male
Non-anaemic
Mild anaemia
Moderate anaemia
Severe anaemia
Female, non-pregnant
Non-anaemic
Mild anaemia
Moderate anaemia
Severe anaemia
Female, pregnant
Non-anaemic
Mild anaemia
Moderate anaemia
Severe anaemia
Total
CDHS 2014

55.8%
28.3%
15.4%
0.6%

66.2%
31.8%
1.9%
0.1%
54.6%
27.3%
17.4%
0.7%
56.2%
37.9%
5.6%
0.3%
38.6%
30.3%
31.1%

46.8%
30.4%
22.4%
0.4%
4.2.4 Sickness and fainting/dizziness
In addition to anthropometrics and haemoglobin levels, workers were also asked questions about their
general health status, including sickness (both with and without stopping work), and feelings of
faintness/dizziness, light-headedness, tired or having cold hands/feet. These are generic symptoms, but
14
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
could indicate health problems including anaemia, malnutrition, low blood sugar (hypoglycaemia), poor
circulation, or reaction to environmental elements (such as cleaning agents). If untreated, these symptoms
could lead to fainting or loss of consciousness.
Nearly half (46.5%) of all workers had felt dizzy, light-headed, tired, or had had cold hands/feet at some
point in the month preceding the third survey interview. Although the number of workers with these
symptoms is substantial, there appear to be few immediate effects, as less than 1% of workers (0.3%)
reported actually fainting at work in the month before the final interview.
One-quarter of all workers (24.8%) reported taking time off work for illness in the last month before the
third interview, taking an average of two days (mean 1.9) off of work when sick. A further 17.5% of workers
felt sick for an average of two days (mean 2.1) in the last month, but still attended work. The scope of this
study does not include the reasons for illness or time off, such as occupational safety and health accidents,
or other conditions of sick leave (paid/unpaid, provision of a medical certificate, etc.).
4.3 Nutritional characteristics
To understand workers’ health in combination with food provision, the nutritional profiles of garment
workers were analysed to find out where they may be weakest, and to understand how a food provision
intervention may possibly improve nutrition.
A precise measure of workers’ food intake in kilocalories is the best way to describe their food
consumption. However, this method is difficult to implement and time-consuming as it would require
following workers for an extended period of time. Thus, several indicators have been built by international
agencies such as the World Food Programme (WFP) and Food and Agriculture Organization (FAO) to help
describe individual and group nutritional profiles. These questionnaires generally record information on
food intake, food diversity and food security (access to food, food quality, etc.), are easily implementable,
and replicable. They include measures of daily and weekly dietary diversity and food consumption, and
specific metrics designed to judge respondents’ food access and security.
4.3.1 Typical daily diet
By calculating the proportions of respondents who reported consuming at least one food from each food
group in the last 24 hours, a typical daily diet was constructed for all non-pregnant female workers. In this
section, the non-aggregated food groups were taken into account to describe this possible daily diet in as
much detail as possible. The typical daily diet presented in Figure 1 is similar across survey rounds7.
The typical non-pregnant female worker consumed food from nine different food groups in the previous
day, although one of these groups is spices, beverages and condiments. This category is usually not taken
into account, as these items are generally eaten in very small quantities and thus their nutritional impact is
considered negligible. Besides spices and condiments, the primary food consumed by nearly all workers is a
cereal; usually rice. Dark green, leafy vegetables (such as kale and spinach) and flesh meats (such as pork,
chicken and beef) are also commonly eaten by the large majority of workers (over 80%), along with oils and
7
Workers who always ate the food provided by treatment factories had slightly more dietary diversity at the third
survey than other workers.
15
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
fats (such as cooking oil). Most workers also consumed fish and other fruits and vegetables daily, along
with sweets.
Despite the common presence of meats and oils, there is a notable lack of nutritional diversity, including
important foods such as those rich in vitamin A, eggs, milk and dairy products. These nutritionally rich foods
were eaten in the last day by less than half of all workers in factories. Part of this lack can be explained by
the Asian diet, which generally eschews milk and other dairy products (such as cheese). However, the daily
diet information does not consider the frequency or overall value of the foods consumed, which is better
addressed by the indicators of food consumption below.
Figure 1 Daily dietary diversity of all non-pregnant female workers in the 24 hours before the final survey (2015)
4.3.2 Food consumption
The weekly food group consumption analysis gives a good indication of the dietary diversity among the
workers surveyed. In looking at daily food consumption, eight food groups are taken into account in this
analysis: staples; animal proteins; oils; vegetables; fruits; sugar; pulses; and milk. All along the study,
workers consumed foods from an average of six groups (6.4 in 2015), which shows an acceptable amount
of dietary diversity when only considering this indicator.
Next, the food consumption score (FCS) was calculated, taking into account dietary diversity, frequency of
consumption, and a food’s nutritional value, using the methodology developed by the World Food
Programme (WFP). FCS considers nine food groups, including a condiment group (which is not part of the
score calculation), and ranges from 0 to 112. An FCS above 35 is considered acceptable.
16
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Workers in the study had average FCS scores of 57.5 in 2015, with a minimum FCS of 26. Nearly all workers
(98.4%) had an acceptable FCS in 2015 (See Table 4). Only around 2% of workers had borderline FCS levels.
Table 4 FCS categories
Variable
FCS categories
Poor (<21)
Borderline (21.5 - 35)
Acceptable (>35)
Total
Total
0.0%
1.7%
98.4%
100.0%
The FCS also provides the ability to examine the weekly food consumption and dietary diversity of garment
factory workers in factories surveyed (Figure 2). The average worker, with an FCS of 57.5, consumes food
from all eight food groups each week (as well as spices/condiments, which are not included here). The basic
weekly diet for workers with the lowest FCS was mostly composed of staples (rice, bread, etc.), animal
proteins (meat, fish, eggs), oil and some vegetables. Sweets/sugars, fruits and pulses were consumed in
very limited frequencies by respondents with the lowest FCS scores. Vegetable, meat, oil and sugar
consumption increased as FCS increased. Fruits, milk and pulses were usually only consumed by factory
workers with FCS higher than 50 or 55.
Figure 2 Weekly food consumption by FCS categories, for all workers at the final survey (2015)
4.3.3 Food security
The FCS indicators do not consider workers’ perceptions of the quantity and quality of the food they eat, or
the precariousness of their food situation. For these indicators, the food insecurity access scale (FIAS) was
used. FIAS was first proposed by the Food and Nutrition Technical Assistance project (FANTA; funded by
USAID) in 2007 as a way to quantify respondents’ feelings of anxiety or uncertainty about food, and
perceptions of food quantity and quality over the past four weeks (one month). Although usually calculated
17
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
at the household level, this indicator was calculated for individual garment factory workers as it easily
captures the required information and provides an additional approach to the issue of food security and
access for these workers.
The majority of workers experienced no food insecurity in the last month before the final survey, with each
FIAS condition experienced by a maximum of only one-quarter of workers (27%). The most common food
insecurities were worrying about having sufficient food, and not being able to eat preferred foods. The
most severe FIAS conditions were also the least mentioned by workers; only around 1% of workers
experienced having no food to eat and going to sleep hungry in the last month.
Taking into account both FIAS condition occurrences and their corresponding frequencies, the categories of
food insecurity were established. FANTA 2011 groups food insecurity into four categories, based on a
combination of frequency and prevalence of different domains: food secure; mildly food insecure;
moderately food insecure; and, severely food insecure (Figure 3).
Among all workers, three in five (61%) were considered food secure in 2015, with few or no worries about
food security and access. A further quarter (22%) had mild food insecurity. Around one in six workers (17%)
had moderate or severe food insecurity.
Figure 3 Food insecurity categories among all workers
5. Food Provision
To understand a possible relationship of factory food provision with workers’ health and nutritional status,
food was provided in four treatment factories. In this section, the different food provision methods and
indicators are detailed. The results in this section are thus only from the treatment factories and their
workers.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
5.1 Food provision - different approaches
The purpose of this research study was to understand the effect (if any) of food provision on various
aspects of the lives of garment factory workers, not to evaluate the implementation process itself. The food
provision programs were designed and implemented individually within each factory, sometimes with the
support of individual brand partners and BFC, as well as food service providers. Factory involvement and
participation in this study was entirely voluntary, resulting in unique food provision designs within each of
the four treatment factories:



One factory provided a full meal to workers, sourced from a local catering company and partially
prepared on-site. This meal included unlimited rice and a main dish for all workers, which changed
regularly. This meal was provided at lunchtime (11am - 12pm) for workers on the day shift, with an
additional meal provided to nightshift workers at midnight. This factory also constructed an on-site
food preparation facility and canteen.
One factory provided a snack to workers in the afternoon (2pm), which consisted of a soup-like
dessert (bong-aihm) or fried noodles, provided by a local catering company and prepared off-site.
The other two factories provided a pastry (with or without filling, which alternated daily) and bottle
of water when workers arrived for work each morning. These were provided by a local bakery in
sealed plastic packaging, which gave workers the option of eating it throughout the day.
Interestingly, the reported costs for each food provision program were similar; around 2,000 KHR
(0.50 USD) per worker per day. All factories provided food every day that production staff worked (six days
a week; Monday through Saturday). Because of the similarities of costs and distribution, the selection of
food provision programs appears to have depended on the motivation of factory management to engage in
the set-up and maintenance of the program, and their views of how such a system would be established
and run on the production site.
5.1.1 Nutritional content
The nutritional content of the food provided by these factories varied considerably, depending on the type
of food provided in relation to the food provision method (Table 8). Food analysis was conducted by the
Industrial Laboratory Center of Cambodia (ILCC) after a single serving of each food provision was collected
from the factories or caterer. Micronutrient content analysis was not available8.
Table 5 Caloric content of food provisions, by type of food provision
Food Provisions
Full meal
White rice
Soup (somlaw majjou
braw-lut)
Energy
(kcal/100g)
Oil & Fat
(% M/M)
Starch
(% M/M)
Sugars (as
saccharose;
% M/M)
Protein
(% M/M)
182.66
0.10%
41.81%
0.0%
3.63%
19.92
0.32%
0.2%
1.27%
2.79%
8
ILCC is the only option available in Cambodia for food calorific testing. Food testing in Thailand is possible, but the
implied logistics would not have been ideal for accuracy. Instead, the standard parameters to measure nutritional
values from a list provided by the ILCC lab were used. Because the calorific value was deemed the most relevant for
the scope of the study, the focus was on these related parameters, as displayed in Table 5.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Food Provisions
Soup (jap-chai)
Afternoon snack
Fried noodles
Dessert
Morning pastry
Plain (no filling)
With filling
*M/M = mass/mass
Energy
(kcal/100g)
Oil & Fat
(% M/M)
Starch
(% M/M)
Sugars (as
saccharose;
% M/M)
Protein
(% M/M)
37.56
1.24%
0.43%
1.8%
4.38%
127.66
94.76
0.3%
0.12%
20.95%
5.55%
3.01%
16.74%
7.28%
1.13%
145.44
294.5
0.28%
5.94%
20.25%
25.24%
4.29%
26.08%
11.19%
8.94%
Because food provision was provided and funded directly by the factories, allowing them to choose the
food was necessary. As can be seen above, this led to variations in the caloric content of the different food
provision interventions. Given their caloric and nutritional differences, the different interventions are likely
not to have the same effect on workers’ health, nutrition and diet or on their socio-economic situation.
5.2 Participation in food provision
At the second and third data collection point, a module was added to ask about the treatment factory
workers’ perceptions and utilisation of food provisions. One year after the start of food provision, half of
workers (51.3%) were still regularly eating the food provided by the factory (six times per week, or every
workday). Seven percent of workers were not eating the food at all; the rest ate the food between one and
five times per week. The average worker ate the food 4 times per week (mean 4.3; median 6). The uptake
of food in the factory that provided the hot lunch was the highest.
The large majority of workers (87.1%) were satisfied with the food provided by factories. Workers were less
satisfied with the taste (69.9%) than the quantity (84.3%) and overall distribution of food (90.5%). Nearly all
workers (91.2%) in treatment factories reported that they wanted food provision to continue, with the
primary reason being that it helps workers to save money.
Among workers that did not always eat the food, the primary reason for not eating the food provisions was
a dislike of the food, mentioned by over two-thirds of respondents (69%) during the final survey. The
second most common reason was that the workers were not hungry at the time that the food was
provided, mentioned by around one in six workers (17.9%). Other reasons included not having enough time
to eat the food provided (6.3%), and not having enough food for all workers (1%). The workers in the
factory that provided the hot lunch were also concerned about the hygienic standards in which the food
was prepared.
5.3 Perceptions of food provision
Treatment factory workers were also asked about their perceptions of the impacts of food provision on
their socio-economic, health and work status. Initial indicators collected during the second survey showed
that approximately half of workers (40% - 50%, depending on the indicator) thought food provision was
having a positive effect on their food budget, work attendance, with little effect on their health (Table 9).
20
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
The number of workers reporting health effects was minimal; over 95% of treatment workers reported no
perceived health effects. One year after the start of the program, the positive perceptions of food provision
appear to have been reduced. This may be because workers have normalized the effects and no longer
notice them in daily life. The positive impacts on health appear to have risen slightly, although again the
number of workers reporting any impact on their health is minimal. These results support the findings from
other indicators that the benefits of food provision were more noticeable over the short term than the long
term. A possible explanation for the health finding is the self-reporting method and the questions asked;
workers were asked about their health in the month prior to the survey. The food expenditures and work
attendance findings could possibly be impacted by the fact that the final survey was conducted in June, a
hot and rainy month and shortly after Khmer New Year.
Table 6 Perceptions of food provision as reported by treatment factory workers, from the second to the third
survey (Dec. 2014 – June 2015).
Spending on food
Less spending
More spending
Work attendance
Better
Worse
Health effect
Better
Worse
Second survey
Third survey
55.5%
3.5%
42.7%
4.7%
40.3%
0.3%
16.8%
0.3%
0.3%
4.4%
0.7%
3.0%
6. Methodology
One of the purposes of this study was to look at the potential effects of food provision on garment factory
workers’ health. This was approached through a quasi-experimental research design. This design
incorporated two experimental research components: (1) a longitudinal sampling methodology, including a
baseline where the initial pre-intervention conditions were measured, and a second and third survey where
the same conditions were measured among the same respondents during and after the intervention;
(2) selection, within the target population, of a treatment group which received the intervention, and of a
control group which did not. As participating factories volunteered for the study and decided themselves if
they would provide food, and the type of food given, a truly random separation of treatment and control
groups was not possible. Within participating factories, workers were randomly selected from among all
workers. The findings were weighted for probability of worker selection in each factory, and are
representative of eligible workers in all participating factories (13,352 eligible workers in total), as well as
each subgroup (treatment/control, male/female, etc.).
Because this study is longitudinal, the same workers interviewed at the start of the study were recontacted for the second and third surveys. From an initial sample of 3,900 workers in 10 factories (six
treatment factories and four control), 1,695 workers in eight factories (including four with food provision)
were successfully interviewed across all survey rounds. The effect of factory worker attrition on the study
21
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
results was accounted for in the initial methodology and sample design (at a rate of 5% per month, which
was the average turn-over for the sector cited in Lautier 2013).
6.1 Data collection timeline
At the start of the survey, all treatment factories were informed about the schedule for the data collection,
and about the importance of starting food provision as soon as possible after the conclusion of the first
data collection phase in their factory (approximately the end of May 2014). The second survey was
conducted in Dec. 2014. This coincided with between 6.0 and 6.4 months of food provision in three of the
treatment factories. The final data collection was completed six months after the second survey, in June
2015. The survey was implemented in the exact same sequence of factories as the second survey, to ensure
the same period of food provision implementation in each of the treatment factories.
6.2 Instrument and indicators
The instruments for this study were designed to measure changes in the indicators developed from the
initial hypotheses. Topics covered in the questionnaire included indicators on the worker characteristics
described in section 3.
The IDDS, FIAS and FCS sections of the questionnaire were modified from templates developed for nutrition
surveys conducted by the Food and Agriculture Organization (FAO), USAID Food and Nutrition Technical
Assistance project (FANTA) and World Food Programme (WFP), respectively.
6.2.1 Anthropometric data and blood testing
In addition to the quantitative questionnaire, anthropometric data was collected from respondents by data
collectors who were trained and had previous experience in conducting anthropometric measurements for
social research. As haemoglobin testing involved blood samples, specialized staff who had experience and
prior training in blood collection were recruited for these positions. The same blood testing staff were
recruited for the first, second and final survey, and provided with additional training in the specific
equipment, blood testing and safe handling procedures used during this study.
6.3 Data management (entry and analysis)
After the data was collected, it was entered into a data entry tool using CSPro (Census and Survey
Processing System, version 5.0) software by trained data encoders. All questionnaires were entered twice
by different data encoders, reconciled, and checked and verified for inconsistencies.
Despite the exclusion of two treatment factories at an early stage of the study, and the loss of more than
1,600 of the selected workers due to factory turnover, the final sample size of 1,669 workers was sufficient
to provide findings representative of the population of workers in the remaining eight target factories, with
a confidence level of at least 90%, and a margin of error of at worst ±10% (p<0.1). That is, there is
reasonable certainty that 90% of garment workers in these factories have experiences that are within 10%
of the survey findings. Because many of the findings are disaggregated by different groups (treatment and
control factories, male and female workers, etc.), the confidence level and margin of error may change for
each indicator. These changes in confidence have been taken into account when analysing the data.
Statistically significant results in this report have been marked with either an asterick or p value; * or p<0.1
22
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
for a 90% confidence level, ** or p<0.05 for a 95% confidence level, and *** or p<0.01 for a 99%
confidence level.
To understand the effects of food provision on the treatment factory workers, the key quantitative
indicators – the variables the most likely to be impacted by food provision – from the first, second and final
survey rounds were analysed using a difference-in-difference (DID) design. DID shows changes in the
representative treatment and control populations over time, and can determine whether changes in the
treatment group differ significantly, or are consistent with, the changes in control. There are a number of
steps involved in this process. First, the trends for each indicator in both the treatment and control groups
were plotted over the three survey rounds. Assuming that the measured indicators in both treatment and
control factory workers would have similar trends over time if there was no intervention, any changes in
the control group can be considered to mirror changes in the treatment group in the absence of food
provision. Then, the situation that might have happened in treatment groups in the absence of food
provision was examined by plotting the counterfactual, which is the trend among workers in control
factories applied to the treatment group at the start of the research (Figure 6).
Figure 4 A model of difference-in-difference analysis (Note: s=1 is the control group at the start and s=2 is the
treatment group at the start. Source: Wikipedia. Used under Creative Commons license.)
6.4 Limitations
There are many factors which can limit the effectiveness of a multi-year impact study such as this. First,
because the sample factories were not randomly selected and factory food programs were not uniformly
implemented (factories volunteered to be included in the survey, decided whether or not to provide food,
and selected the types of food provided differed), caution is needed when making any inferences with the
general population of garment workers. Despite differences in food types and quantities, all treatment
factories analysed at the final data collection point provided the same foods every workday for the same
workers, providing consistency throughout the implementation period.
While it would have been best for the study to randomly separate workers in each factory into treatment
and control groups (where one group of workers receives food during the study, and the other group
receives a delayed or alternate incentive, such as a cash supplement at the end of the study period), in the
interest of equity factories decided that all workers in the treatment factories would receive the same food
provision at the same time. However, this means that some specific differences between the treatment and
control factories may have also influenced the results of this research.
23
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Much of the data collected for this three-round survey was self-reported by respondents, who may have
over-reported or under-reported their status on indicators such as their food consumption occurrences
and/or frequencies during the previous day, week or month, for a variety of reasons (forgetfulness, loss of
face, hope of additional support, fear of repercussion, etc.). Anthropometric and factory-provided data
attempted to control for some of these inaccuracies, by providing unbiased metrics on health and
productivity indicators.
Efforts were made to understand how food provision could affect individuals’ personal and professional
lives, as well as any factors which would obscure the effects of food provision. However, a number of
confounding factors were not accounted for in the study design. For example, micronutrient analysis of the
provided food was not able to be conducted, and the actual food provided, especially the snack and bread
and water, were unlikely to lead to significant changes in BMI, MUAC or haemoglobin levels within the
study period.
Another set of indicators, mainly related to management systems such as contracting practices in surveyed
factories (provision of FDCs or unspecified duration contracts, payment of sick leave, monetary incentive
systems and quality of general working conditions, including harassment) were not covered by the study. It
is expected that these indicators also contribute to physical health and nutritional situation.
The different food consumption, diversity and security indicators calculated in this study are assumed to be
applicable across time, social context, location, population, etc. However it is clear that there are other
external parameters that could influence the results (such as culture, socio-economic status, geography,
etc.). Nevertheless, the survey was conducted in a sufficiently short time period, in a sufficiently
homogeneous sector (project-targeted garment factories) and within a sufficiently homogeneous
population to consider that the indicator results are comparable between the control and treatment group.
The Mission Plus Hb Hemoglobin Testing System was used to analyse garment factory workers’ blood
samples. All units used in all survey rounds were identical and were purchased at the same time. According
to the manufacturer’s specifications, these machines have a standard margin of error of ±4%, meaning that
results for the same blood sample may differ slightly from one machine to another. Statistical tests on this
data by factory and data collection team showed that there were no statistically significant differences
between the mean haemoglobin level values recorded by the different machines.
7. Highlights of Findings
This section summarizes the significant findings of the study, and classifies the potential implications of
food provision depending on the nature of the variable considered (health and nutrition indicatorsr). The
analysis of the data collected before the start of food provision showed that the garment worker
populations in treatment and control factories were statistically similar across nearly all indicators9.
9
The few significant differences between the groups were not expected to influence the findings on food provision, as
treatment and control groups were not compared across individual points, but across trends over time (via the DID
analysis).
24
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
7.1 Food consumption, food security and health
Workers in the study had average FCS scores of 57.5 in 2015, a slight increase from the first survey scores
of 55.7, with a minimum FCS of 26. From the first to the second survey, treatment factory workers showed
significant improvements in FCS10 and FIAS scores, relative to workers in factories without food provisions
(p<0.01). Also, from the first to the second survey, treatment factory workers became significantly more
food secure than control workers (p<0.05).
Workers in treatment factories who always ate the food provided by factories had slight improvements in
dietary diversity than control factory workers, but this did not translate into significantly increased food
consumption or food security scores over the total duration of the study11. Workers in treatment factories
who always ate the food provisions also had higher diversity of food consumption than treatment workers
who occasionally or never ate the food provisions (FCS scores of 6.5 and 6.3, respectively). The treatment
factory that provided workers with a full meal had no workers with severe food insecurity at the third data
collection point, unlike all other treatment and control factories. The number of loans taken to pay for food
reduced significantly over the course of the study for the treatment factory workers (and increased for the
control group; a significant difference at p<0.05), which could be a positive effect from the food provision
intervention.
Figure 7 shows the proportions of garment factory workers that experienced food insecure conditions in
the last month before the final survey. The majority of workers experienced no food insecurity; with each
FIAS condition experienced by a maximum of only one-quarter of workers (27%). The most common food
insecurities were worrying about having sufficient food, and not being able to eat preferred foods.
Figure 5 Proportion of workers experiencing FIAS conditions in the month before the final survey
10
The percentage of treatment workers with an acceptable FCS score significantly increased relative to control factory
workers from the first to the second survey.
11
From the first to the second survey, treatment factory workers significantly increased the number of food groups
they consumed food from, relative to control factory workers.
25
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Free food provision did not significantly change treatment workers’ BMI or anaemia rates, possibly because
the foods provided did not contain sufficient caloric or micronutrient contents) to increase workers’
weights or haemoglobin levels. Interestingly, anaemia levels increased throughout the study across all
treatment and control factories. It should be noted that the anaemia levels of the overall population have
generally increased between 2010 and 2014 as well, per CDHS data. As discussed earlier, anaemia is a
complex physiological issue, with many influencing factors. If anaemia is not caused by malnutrition, but by
haemorrhage, chronic diseases, malaria, parasitic infection or genetic disorders, interventions other than
food and micronutrient supplements may be needed to improve haemoglobin levels. More research would
therefore be needed on the specific causes (both physiological and behavioural) of anaemia among this
population.
When examining self-reported health events, the DID analysis suggests that the food provision may have
had a short-term impact on dizziness/fainting, as rates dropped after the first six months of food provisions
(p<0.05), but returned to the pre-treatment values for the treatment group by the time of the final survey.
This may be explained by the time periods of data collection, which measures the respondent’s experience
in the month preceding the survey. The weather conditions and production load in April, May and June (the
timing of the first and final surveys) can be rather different from those in November and December (the
timing of the second survey).
8. Discussion and Lessons Learned
The research led to a number of findings, many of which are also important starting points for further
discussion and research. It should be reiterated that the findings need to be considered cautiously, taking
into account the limitations of the design of the interventions and research.
8.1 Analysis and recommendations
Food is an important element of a strategy to improve workers’ welfare. At the same time, the implications
of a food provision program also depend on individual organizations and process-related factors: the
nature of the food provided (quality and quantity); hygienic food preparation; the time of day and time
allocated for food provision; worker feedback systems, and other elements. As can be seen from the results
in this study, providing food is more complex than it may initially appear. The nutritional and micronutrient
values of food can be an important factor in the health and nutrition outcomes of an intervention. For
future research, specific micronutrients/fortified foods (i.e., iron folate supplements to reduce anaemia,
vitamin A supplements, fortified oils, rice and iodised salt) could be analysed prior to food provisions to
devise meal plans that best address the health issues of workers. Specific areas of focus could also include
maternal health, or strategies to reduce dizziness/fainting at work.
When considering the design of food program interventions, it would be important to ensure that the food
provided by factories is nutritionally rich, sufficiently diverse and suited to beneficiaries’ tastes. This would
help improve dietary diversity and micronutrient consumption, and increase uptake among workers.
Workers are appreciative of the food provided in general. Also, working in partnership with other factories,
brands and institutional stakeholders increases the success rate of an intervention. Knowledge sharing,
26
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
technical support, and training among industry players can significantly enhance the quality of food
programs, and improve the health status of workers in their supply chains.
Providing food is only one component of a comprehensive nutrition program, which is reliant on continued
support from outside influences (such as factory management), and subject to changes in factory turnover.
Improvements in workers’ understanding of positive health behaviours, including how to make appropriate
food choices for better health and nutrition, would help workers to make positive changes in their own
lives over the long term, and would also benefit their children and other family members. There are
indications that garment workers may have a low level of awareness on what constitutes a balanced and
nutritious diet, as indicated by the findings on dietary diversity which show that workers eat mainly meat,
rice and condiments. It has to be noted that workers expressed their concerns about the hygienic
circumstances under which foods were prepared and available outside factories. The fact that more
workers are overweight than underweight may also be a sign of low levels of understanding about healthy
food choices.
Factories, working together with partners including the Ministries of Health and Labour, brand buyers,
GMAC, international organizations and NGOs, can do more to ensure that workers are better informed on
the importance of good nutrition and dietary diversity. To this end, they could consider providing training
on nutrition, dietary diversity and hygiene. This could also help increase factory food provision uptake by
workers. In some factories in Cambodia, colourful food pyramid posters have been used as a tool to
promote healthy eating. These posters can be displayed in canteen areas to educate workers on making
healthy, relevant and affordable choices on good nutrition.
Anaemia rates among female garment workers (pregnant and non-pregnant) are worse than in the general
population and increased throughout the study. It should be noted that the anaemia levels of the overall
population have generally increased between 2010 and 2014 as well, per CDHS data. This situation clearly
requires more discussion and research to find an appropriate solution. Anaemia can result from a
nutritional deficiency of iron, folate, vitamin B12, or other nutrients. This type of anaemia is commonly
referred to as iron-deficient anaemia, and is the most widespread form of malnutrition in the world (CDHS
2014). However, anaemia can also be the result of haemorrhage, chronic diseases, malaria, parasitic
infections, or genetic disorders such as haemoglobin E trait, beta-thalassemia, and alpha-thalassemia
(CDHS 2014). Some of these genetic disorders may be more prevalent in the Southeast Asian region, but
more research is needed to draw conclusions on the different causes of anaemia in Cambodia.
To address the high levels of anaemia among workers, specific interventions could be considered, but these
would have to be grounded in a more in-depth investigation of prevalent causes of anaemia. Depending on
such causes, strategies could include iron supplements, medication to reduce malaria or parasites, or
multivitamin supplements and provision of fortified foods (rice, oils, salt) to help improve anaemia caused
by malnutrition or haemorrhage, malaria or parasitic infection, or chronic diseases, respectively. As there
are additional causes of anaemia (including genetic disorders), identifying a specific intervention would
require working with a nutritionist or nutrition support program, such as WFP, to identify the most
prevalent types of anaemia in specific worker groups, and appropriate interventions.
27
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
The BMI scores for workers in this study revealed that nearly one in four workers (24.0%) are considered
overweight or obese, and are at increased risk of contracting lifestyle or noncommunicable diseases such as
diabetes. Further research could investigate the spectrum of reasons (understanding of nutrition, eating
habits, access to food, sedentary nature of their work, etc.) for these relatively high levels of overweight
and obesity, and the effect and feasibility of exercise, health and nutrition classes for garment workers.
Exercise classes should also be kept in mind when considering welfare interventions in factories, as they
could be relatively easily accommodated and have a significant positive impact on the health and quality of
life of garment workers. These could consist of voluntary group aerobics classes, which are popular with
many Cambodians and are commonly conducted in parks and open spaces throughout Phnom Penh and in
many large cities. Per WHO recommendations (WHO 2010), 20 minutes of exercise per day can reduce the
risk of lifestyle-related noncommunicable diseases, such as diabetes, which is rapidly increasing in
prevalence in Cambodia.
8.2 Lessons learned in food provision implementation
In the course of food provision implementation by factories participating in the research, as well as by
another factory that provided food but started the intervention too late to be included in the target group,
a number of lessons were learned about the actual food provision interventions. These were drawn from a
number of sources, by both Angkor Research and BFC, and include12:

Ensuring food is flavourful, nutritionally rich and culturally appropriate. The possible benefits of
food provision and the food provision uptake are influenced by the type of food provided, including
its nutritional content, as well as its taste and the scheduling of food provision. Some workers in
factories with early morning food provision did not eat the food provided (those that provided
pastry) because they were not hungry and regularly skipped breakfast; others preferred eating rice
(a traditional Khmer breakfast) or a savoury food in the morning. Workers in all factories
complained about a lack of variety, as the menus usually varied between only a few (2-3) dishes.
Providing sufficient varieties of foods to keep workers engaged, while maintaining nutritional and
hygienic standards, is a challenge that food providers face everywhere, but one that pays off in
higher consumption and worker satisfaction rates. Improving the diversity of the menu –
occasionally dropping and adding foods, providing savoury and sweet options, and foods which are
culturally familiar – is vital to a long-term, successful food provision program. Getting the input of
the workers on the types of foods and times they would prefer to eat also helps ensure buy-in and
ownership of workers in the program.
Dietary diversity is a key component to improving the nutritional status of garment workers and
can be achieved through regular consumption of a variety of nutritious foods. Dietary guidelines13
should address the dietary needs of each country’s population, taking into consideration the
following:
12
BFC collected additional feedback in March, April and December, 2015, through qualitative interviews with
employers and workers as well as Hagar Catering Facilities, independently from the main factory and worker data
collected by Angkor Research.
13
See Food and Agriculture Organization (FAO) Food-based dietary guidelines, available
http://www.fao.org/nutrition/education/food-dietary-guidelines/background/en/ [accessed Dec. 14, 2015].
at
28
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
o
o
o
o
A range of meals that include all four food groups;
Macronutrients (carbohydrates, protein, fats);
Micronutrients (vitamins and minerals);
Protein-rich foods from a good balance of vegetable and animal sources, for example
increasing intake of fish and beans/peas;
o Appropriate amounts of vegetable and animal fats/oils. Sesame and peanut oils are
recommended;
o Avoiding sweet and salty foods. Iodized salt is recommended;
o Daily intake of fruits and vegetables;
o Food safety during selection, processing and cooking of food.
Ensuring that the food provided by factories is nutritionally rich and sufficiently diverse can be
achieved by working with a catering company with experience in nutrition.


Establish communication channels aimed to promote worker feedback. Mechanisms designed to
gauge worker satisfaction levels with canteen services can have positive benefits on worker morale
and motivation, reduce worker turnover, and importantly, help ensure that workers eat the food
provided by the factory. Feedback systems can help factory management understand workers’ food
preferences and take steps to implement their constructive comments and suggestions. These
feedback mechanisms can enhance satisfaction levels and increase the likelihood of food uptake by
workers, and could include:
o Food committees can be an important platform for workers to provide feedback on
factory meal programs. By bringing together factory management and worker
representatives, food committees provide employers the opportunity to hear directly
from workers about their food preferences. Food committees can meet on a monthly
basis and allow workers and management to discuss, and even improve, factory meal
programs in an organized, systematic and collaborative way.
o Surveys are an effective mechanism to gauge workers’ satisfaction with meals, and to
better understand their food preferences. Surveys should be conducted in the local
language and easy to understand. Findings should be followed up by the factory
management to improve the program. If literacy levels are low, surveys can be
conducted orally.
o Inform workers of meals ahead of time in factories. Weekly menus can be posted, for
example, near the factory entrance, informing workers to what is being served ahead
of time. Workers can even inform the factory ahead of time if they will eat the food on
a certain day. This could help factories and catering providers to save money and
reduce food wastage.
o Good communication between management and catering provider. Factory
management should regularly share worker feedback on preferences, quality and
quantity, with the catering company or food supplier they are working with. Good
communication between the factory and catering service strengthens partnerships and
contributes to the overall successful delivery of food provision programs.
Addressing concerns about the logistical and organizational impacts of different types of food
provision. Many factories worry about the disruptive effects of the food provision program on their
workday (e.g., time for set-up, distribution and cleaning, monitoring efforts by factory
management, etc.). These concerns, as well as cost, can lead to a decision to provide
29
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories


snacks/pastries instead of a full meal. It should be noted that an efficient canteen service can help
minimise and even eliminate potential disruptions. However, in a country without a history of
factory-provided food programs, there is the need for increased awareness on food provision and
good practices in terms of logistic arrangement and service design.
Ensure hygienic food preparation. According to the World Health Organization (WHO), safe
drinking water, sanitation and hygiene (WASH) services have an important positive impact on
nutrition. The global nutrition community has repeatedly called for greater attention to, and
investments in, WASH as a means to improve nutrition outcomes (WHO et al 2015). Internationally
agreed upon WASH activities aimed at food hygiene can be instructive for garment factories and be
integrated into canteen services for better health outcomes for workers. Factories with canteen
services can consider following recommended international WASH guidelines on hygienic food
preparation, including:
o A clean environment is essential for food preparation, cleaning key surfaces and
utensils, protecting food preparation areas from dust, insects, pests, etc.
o Separate raw and cooked food;
o Cook food thoroughly;
o Store food at safe temperatures;
o Use safe water and raw materials;
o Keep cooking surfaces and floors clean, with cooking surfaces and floors cleaned
regularly with soap and water;
o Ensure that both food provision staff and clients (factory workers) wash their hands
thoroughly before preparing, handling or consuming food. Hand-washing stations can
be established for these purposes inside canteens.
Catering companies and food handlers working in canteen services should be equipped and trained
with the necessary skills and knowledge on hygienic food preparation, such as the HACCP system14.
Originally developed by Pillsbury Company in the U.S., the HACCP is comprised of seven principles15
and now widely used in the food industry at the international level, including catering services in
Cambodia. HACCP is designed to identify and control potential problems before they occur and is
considered to be the best system currently available to reduce and prevent foodborne illness.
Consider serving logistics. It is recommended that large enterprises (for example, those with over
1,000 workers) that are just starting a food provision program conduct a training or rehearsal with
workers on procedures of lining up, collecting trays/plates/utensils and food disposal. Management
should consider timing how long the process takes to improve efficiency. Involvement of line
leaders is key to ensuring successful and smooth operation. Allow pregnant workers to eat first.
If factories consider providing food to their workers, a number of logistical recommendations to set up
canteens can be made:
14
HACCP (Hazard Analysis and Critical Control Point) is a system that helps food business operators look at how they
handle food and introduces procedures to make sure the food produced is safe to eat. The National Food Service
Management Institute (NFSMI) has developed HACCP-based Standard Operating Procedures in conjunction with USDA
and FDA. For more information see: http://www.food.gov.uk/business-industry/food-hygiene/haccp.
15
See the seven HACCP Principles at http://www.fsis.usda.gov/Oa/background/keyhaccp.htm.
30
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories




Choose an appropriate location. An appropriate location should be selected for the canteen within
or near the factory premises. The canteen eating area should be clean, well lit, and ventilated with
enough tables, chairs and benches for workers. The canteen should allow employees to take a
break from their work in a comfortable environment.
Invest in proper equipment and set-up costs. Equipment needed for on-site food preparation
includes but is not limited to: stoves, rice cookers, refrigerators, freezers, racks, trays, plates,
utensils, cups, and commercial size food warmers. Set-up costs will vary from factory to factory,
and depend upon the factory’s requirements, including existing space, seating area, equipment and
various provisions. Set-up and purchasing costs may range anywhere from 20,000 USD to
50,000 USD, depending on the needs of each factory.
Serving in shifts. In factories with large numbers of workers, arrange for workers to eat at different
times, thus reducing the need for more spacing. Provide enough time for workers to eat, relax and
socialize; typically one hour.
Food purchase, preparation and clean-up. In factories, caterers may work with up to two to three
suppliers. Suppliers typically deliver all fresh vegetables and meats/fish the day before. Food is
prepared on the day of service and must be ready to serve at the start of the (first) meal shift.
o Example, to service hot lunch (to complete before start of lunch break at 11am):
 1 team to cook rice;
 1 team to cook food;
 1 team for set-up (spoons, forks, trays);
 2-3 persons for condiments (cutting chillies, setting out soy sauce and
condiments).
o 6am: Arrival of catering staff
 Rice cooking takes the longest time (1 hour to cook 45 kilos, enough for 300
people) and should start immediately;
 One rice serving: 150 grams (uncooked) rice per person.
o 7-8am: Cooking of food begins
 Cooking time: around 4 hours.
o 11am-1pm: Most catering staff are dedicated to serving lunch to workers and ensuring
rice containers are filled (rice servings are unlimited).
o Clean-up: All staff involved in clean-up and washing for 1st shift and start preparing for
the next shift. Catering companies are typically responsible for collecting and washing
dishes after meals. Factory management can provide oversight to ensure that the
canteen area (floors and countertops), dishes, cups and silverware are cleaned
hygienically every day with soap and warm water.
o Food preparation for following day: after lunch has been served for all shifts and
following clean-up, all catering staff participate in food preparation for the following
day. This involves washing and cutting of meats/fish/vegetables. All food is stored and
refrigerated for cooking the following day.
31
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
9. References
Acon Labs (2014). Mission Plus Hb. San Diego, Acon Labs.
(http://cc.aconlabs.com/Products/ACONMissionHemoglobinandMissionPlusHbHemogl/MissionPlus
Hb.aspx, accessed on 10 Sept. 2014)
Better Factories Cambodia (2012a). Twenty eighth synthesis report on working conditions in Cambodia’s
garment sector. International Labour Office: International Finance Corporation. Geneva, ILO.
Better Factories Cambodia (2012b). Study on the perceptions of garment factory owners on nutrition and
the feasibility for pursuing canteen services in the garment sector in Cambodia. January 2012.
(http://betterwork.org/cambodia/wp-content/uploads/2013/01/Harga-Report.pdf )
Food and Agriculture Organization of the United Nations, prepared by Gina Kennedy, Terri Ballard and
Marie-Claude Dop (2013), Guidelines for Measuring Household and Individual Dietary Diversity.
Nutrition and Consumer Protection Division, Food and Agriculture Organization of the United Nations.
FAO (2015). Food-based dietary guidelines: Background. (http://www.fao.org/nutrition/education/fooddietary-guidelines/background/en/, accessed Dec. 14, 2015).
Food and Nutrition Technical Assistance (FANTA) project (August 2007), Coates, Jennifer, Anne Swindale
and Paula Bilinsky, Household Food Insecurity Access Scale (HFIAS) for Measurement of Household Food
Access: Indicator Guide (v. 3). Washington, D.C.: Food and Nutrition Technical Assistance Project,
Academy for Educational Development, August 2007
Ferro-Luzzi, A and James, WP (1996). “Adult Malnutrition: Simple Assessment Techniques for Use in
Emergencies”. British Journal of Nutrition. 75(1):3–10.
The Harmonised Training Package (HTP): Resource Material for Training on Nutrition in Emergencies,
Version 2 (2011). Module 6 Measuring malnutrition: Individual assessment. NutritionWorks, Emergency
Nutrition Network, Global Nutrition Cluster. (http://www.unscn.org/en/gnc_htp/, accessed 01 Sept.
2014).
International Labor Organization (ILO) (2015a) prepared by the ILO Regional Office for Asia and the Pacific,
“Growth continues for Cambodia’s garment and footwear sector”. Cambodia Garment and Footwear
Sector Bulletin, no. I, July 2015.
International Labor Organization (ILO) (2015b) prepared by the ILO Regional Office for Asia and the Pacific,
“Solid first half of 2015 for Cambodia’s garment and footwear sector”. Cambodia Garment and
Footwear Sector Bulletin, no. II, October 2015.
Lautier, M (2013). Feasibility and Preparation work for the Study on the Implications of Food Provision
services on the Workers’ Health and Productivity in Cambodia’s Garment Factories. Report prepared for
AFD.
32
Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
National Institute of Statistics (NIS), Directorate General for Health, and ICF Macro (2011). Cambodia
Demographic and Health Survey 2010. Phnom Penh, Cambodia and Calverton, Maryland, USA, National
Institute of Statistics, Directorate General for Health, and ICF Macro.
National Institute of Statistics (NIS), Directorate General for Health, and ICF Macro (2015). Cambodia
Demographic and Health Survey 2014, Key Indicators Report. Phnom Penh, Cambodia and Calverton,
Maryland, USA, National Institute of Statistics, Directorate General for Health, and ICF Macro.
United Nations Standing Committee on Nutrition (2000). Adults: Assessment of Nutritional Status in
Emergency-affected Populations. Geneva, SCN.
World Food Programme (February 2008), Food consumption analysis: Calculation and use of the food
consumption score in food security analysis. Prepared by VAM unit HQ Rome. Version 1. © World Food
Programme, Vulnerability Analysis and Mapping Branch (ODAV)
World Health Organization (1995). Physical status: the use and interpretation of anthropometry. Report of a
WHO Expert Committee. Technical Report Series No. 854. Geneva, WHO.
WHO Expert Consultation (2004). “Appropriate body-mass index for Asian populations and its implications
for policy and intervention strategies”. The Lancet 2004; 363:157-163.
WHO (2008), Worldwide prevalence of anaemia 1993-2005, de Benoist B et al., eds. WHO Global Database
on Anaemia Geneva, World Health Organization.
WHO (2010). Global Recommendations on Physical Activity for Health. Geneva, WHO.
WHO (2011). Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin
and Mineral Nutrition Information System. Geneva, WHO (WHO/NMH/NHD/MNM/11.1)
(http://www.who.int/vmnis/indicators/haemoglobin.pdf, accessed 01 Sept. 2014).
WHO (2013). Women’s health. Fact sheet No. 334, updated 2013.
(http://www.who.int/mediacentre/factsheets/fs334/en/#, accessed 01 Sept. 2014)
Geneva,
WHO.
WHO (2014). BMI classification. Global Database on Body Mass Index. Geneva,
(http://apps.who.int/bmi/index.jsp?introPage=intro_3.html, accessed 01 Sept. 2014).
WHO.
WHO, UNICEF, USAID (2015). Improving Nutrition Outcomes with Better Water, Sanitation and Hygiene:
Practical
Solutions
for
Policies
and
Programmes.
Geneva,
WHO.
(http://apps.who.int/iris/bitstream/10665/193991/1/9789241565103_eng.pdf, accessed Dec. 14,
2015.
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Garment Workers’ Health, Socio-Economic Status and Food Provision in Factories
Annex 1: Significant results produced by DID analysis
Parameter
Nutrition indicators
FCS number of food groups consumed weekly
FCS score
Percentage of workers with acceptable FCS
Percentage FIAS domain ‘Insufficient food intake’
FIAS score
Percentage of food secure workers (FIAS)
Health indicators
Average haemoglobin levels (all workers)
- Average haemoglobin levels (male)
- Average haemoglobin levels (non-pregnant
female)
- Average haemoglobin levels (pregnant female)
Percentage of non-anaemic workers (all workers)
- Percentage of non-anaemic (male)
- Percentage of non-anaemic (non-pregnant
female)
- Percentage of non-anaemic (pregnant female)
Percentage of workers going to work while being sick
(last month)
Percentage of workers feeling dizzy (last month)
Percentage of dizziness episodes happening at work
* p<0.1; **p<0.05; ***p<0.01
1
Among workers reporting overtime
2
Among workers who reportedly send remittances
3
Among workers reporting debt
Value of significant results
Short-term changes
Long-term changes
(First to Second Survey)
(First to Third Survey)
+0.3 food groups***
+4.1***
+1.8%*
-13.8%***
-0.75***
+8.7%**
-7.1%**
-0.43**
-
-1.1 g/dL***
-1.9 g/dL***
-1.4 g/dL***
-2.2 g/dL***
-0.9 g/dL***
-1.2 g/dL***
-1.0 g/dL***
-29.6%***
-40.6%***
-1.8 g/dL***
-40.0%***
-54.3%***
-27.9%***
-35.7%***
-14.0%***
-35.0%***
-6.1%**
-
-11.2%***
+13.3%***
-
34