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RESEARCH ARTICLE
Increasing prevalence of overweight and
obesity in Bangladeshi women of
reproductive age: Findings from 2004 to 2014
Tuhin Biswas
1,2
*, Md. Jasim Uddin
1
, Abdullah Al Mamun
2
, Sonia Pervin
1
,
Sarah P Garnett
3,4
1Health Systems and Population Studies Division, icddr,b, Mohakhali, Dhaka, Bangladesh, 2Institute for
Social Science Research, The University of Queensland, Long Pocket Precinct, Indooroopilly, Queensland,
Australia, 3The Children’s Hospital at Westmead Clinical School, University of Sydney, Sydney, Australia,
4Institute of Endocrinology and Diabetes, The Children’s Hospital at Westmead, Locked Bag 4001,
Westmead, New South Wales, Australia
*tuhin.biswas@icddrb.org
Abstract
Background
Overweight and obesity are a particular concern for women of reproductive age. They not
only increase the risk of chronic diseases but they are also associated with adverse perina-
tal, neonatal, infant and child outcomes. The objective of this study was to examine the
trend of overweight and obesity among Bangladeshi women of reproductive age between
2004 and 2014.
Method
This is a secondary data analysis of the 2004, 2007, 2011 and 2014 Bangladesh Demo-
graphic and Health Surveys (BDHS). We determined the age standardized prevalence of
overweight and obesity of women aged 15–49 years, who had their weight and height mea-
sured. Overweight and obesity were determined using the Asian specific BMI cut-offs
criteria.
Result
The prevalence of overweight increased from 11.4% [95% CI: 10.4to 12.5] in 2004 to 25.2%
[95% CI: 24.0 to 26.4] in 2014. The prevalence of obesity increased from 3.5% [95% CI:
3.0to4.2] to 11.2% [95% CI: 10.1to12.5%] over the same period of time. This was seen in all
age groups. However, the greatest increase was observed in women aged 35 to 49 years.
The highest prevalence of overweight and obesity were observed in those women with the
highest education level and wealth, larger family size, living in urban areas and not being in
paid employment.
Conclusion
The prevalence of overweight and obesity among women of reproductive age in Bangladesh
is high and increasing. We speculate that this has the potential to jeopardize the
PLOS ONE | https://doi.org/10.1371/journal.pone.0181080 July 28, 2017 1 / 12
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OPEN ACCESS
Citation: Biswas T, Uddin M.J, Mamun AA, Pervin
S, P Garnett S (2017) Increasing prevalence of
overweight and obesity in Bangladeshi women of
reproductive age: Findings from 2004 to 2014.
PLoS ONE 12(7): e0181080. https://doi.org/
10.1371/journal.pone.0181080
Editor: David Meyre, McMaster University,
CANADA
Received: March 19, 2017
Accepted: June 26, 2017
Published: July 28, 2017
Copyright: ©2017 Biswas et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: The data set of
BDHS-2004 to 2014 is available at the
Demographic and Health Surveys Program. This is
an open sources data- set, which is available on
request at http://dhsprogram.com/what-we-do/
survey/survey-display-349.cfm.
Funding: The author(s) received no specific
funding for this work.
Competing interests: The authors have declared
that no competing interests exist.
improvements that have been made in maternal and infant health over the last two decades.
Evidence based prevention strategies are required to address this serious public health
issue.
Introduction
Overweight and obesity are an increasing public health problem in both developed and devel-
oping countries[1,2]. In 2014, the World Health Organization (WHO) estimated 39% of
adults aged 18 years and over were overweight or obese[3,4]. The prevalence of overweight
and obesity varies widely between countries and tends to increase with income level. Hence,
the WHO Region of the Americas has the highest prevalence and the WHO Region for South-
east Asia the lowest[5]. Nevertheless, with increasing economic development in Southeast
Asia, increasing rates of overweight and obesity have been reported in most countries includ-
ing Malaysia, India and Indonesia[6].
The association between overweight and obesity and increased risk of non-communicable
diseases has been well described[1,2].The prevalence of overweight and obesity also varies by
sex. In contrast to developed countries, more women in Southeast Asia are overweight and
obese compared to men, which in 2013 was estimated to be 28% and 22% for women and
men, respectively[1,4].Overweight and obesity pose an additional concern for women, partic-
ularly of reproductive age. It not only affects the woman’s health by increasing her risk of ges-
tational diabetes, type 2 diabetes and cardiovascular disease, it is also associated with adverse
perinatal, neonatal, infant and childhood outcomes[7].
As like as other developing country, Bangladesh is experiencing a rapid demographic and
epidemiological transition [8–10]which has been associated with increases in overweight and
obesity. In 2011, cross-sectional data indicated that the overall prevalence of overweight and
obesity combined in women who had been or were married was 18%[11], approximately
1.5 times that reported in women aged 20 to 49 years of age in 2007[12]. However, making a
direct comparison in prevalence between years is difficult due to the different age of women in
each study; that is ever-married women compared to women age 20–49 years.
It is important to understand the trends in prevalence of overweight and obesity in women
of reproductive age for current and future generations and to be able to plan appropriate inter-
ventions. To our knowledge this has not been previously described in Bangladeshi women.
Hence, the objectives of this study was to determine the trend of overweight and obesity
among Bangladeshi women of reproductive age (15 to 49 years) using national representative
data between 2004 and 2014 and to examine the socio-demographic determinants of over-
weight and obesity in the same population.
Methods
Participants
This paper analysed secondary data of the Bangladesh Demographic and Health Surveys
(BDHS), 2004, 2007, 2011 and 2014. The BDHS is a cross-sectional, national representative
survey conducted by collaboration between the National Institute of Population Research and
Training (NIPORT), ICF International (USA), and Mitra and Associates. The participants in
the BDHS were selected using probability sampling based on a two-stage cluster sample of
households, stratified by rural and urban areas in the seven administrative regions of
Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
PLOS ONE | https://doi.org/10.1371/journal.pone.0181080 July 28, 2017 2 / 12
Bangladesh [10]. Urban areas are divided into small administrative units known as mahallas
and rural areas are divided into mauzas. Mahallas and mauzas form the primary sampling
units in the first stage of sampling and typically include 100–120 households. In the second
stage, a sample of 30 households is systematically selected from each primary sampling unit.
The detailed protocol and methods were published earlier [13–15]. Data used in this analysis
was based on women of reproductive age (ie 15 to 49 years). Women who were pregnant dur-
ing the survey period or had missing data were excluded from the analysis.
Demographic characteristics, including educational status, involvement in paid work, and
region (district) and place (urban or rural) of residence was collected by questionnaire which
was administered during a face to face interview. Household wealth index is a composite mea-
sure of a household’s cumulative living standard. The index is calculated using household’s
ownership of selected assets, including electricity, televisions and bicycles; materials used for
housing construction; types of water access and sanitation facilities; use of health and other
services, and in health outcomes. It is determined using principle components analysis.
National-level wealth quintiles (from lowest to highest) are obtained by assigning the house-
hold score to each de jure household member, ranking each person in the population by his or
her score, and then divided the ranking into five quintile, each comprising 20 percent of the
population [10,16].
Anthropometry
Weight and height were measured at the participant’s home by trained field research staff.
Weight was measured twice using a solar-powered scale (UNICEF electronic scale or Uniscale)
to the nearest 0.1 kg with light clothing on and without shoes by digital weighing scales placed
on a flat surface. Height was measured two times using a standard clinical height scale with
participants standing without shoes. The average of the two measurements was used in the
analysis.
Overweight and obesity
Asian specific BMI cut-offs were used to define underweight (<18.5 kg/m
2
), overweight
(23.0 to <27.5 kg/m
2
) and obese (27.5 kg/m
2
)[17]. The data collection and anthropometric
measurements were undertaken by trained field staff in the participant’s home.
Statistical analysis
We estimated the prevalence of overweight and obesity in the different survey years according
to age group. The age-adjusted prevalence of overweight and obesity and 95% confidence
intervals (CI) were also calculated. Categorical variables were presented as frequencies and
95% CI. The prevalence of overweight and obesity was presented by age group (15 to 24, 25 to
34 and 35 to49 years) and place of residence. Educational level was stratified into four groups:
no education, primary education, secondary education and higher level education. To assess
the age differences at different time points, we used logistic regression to estimate the preva-
lence odds ratio (POR). All analyses were adjusted for sample design (cluster and sample
weight) and completed in SPSS (IBM, 21).
Ethical approval
Ethics approval for the BDHSs was obtained from the Institutional Review Board of the Medi-
cal Research Council of Bangladesh. Informed consent was given by the participants.
Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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Results
The number of participants and the socio-demographic characteristics of the women in 2004,
2007, 2011 and 2014 are presented in Table 1. Between 2004 and 2014 the number of women
who had primary and above level education increased from 60.5% to 75.6% and the number of
women in paid work increased from 22.6% to 32.4%. Over the same period, the proportion of
large families (ie households who had 5 residents) declined from 67.2% to 57.6%.
The trends in prevalence in overweight and obesity are shown in “Fig 1”. In 2004, overall
11.4% [95% CI:10.4 to 12.5] of women were overweight, which increased by two and half
times to 25.2%, [95% CI: 24.0to 26.4] in 2014. The increase between 2011 and 2014 was 6%.
The overall prevalence of obesity increased almost threefold over the same time period, from
3.5% [95% CI: 3.0 to 4.2] in 2004 to 11.2% [95% CI: 10.1 to 12.5%] in 2014.Similar to
Table 1. Demographic characteristics of the participants, 2004 to 2014.
Socio-demographic variables 2004 (n = 10603) 2007 (n = 10127) 2011 (n = 16352) 2014 (n = 16624)
Age (years)
15–24 3342 (31.5) 3041 (29.6) 4670 (28.0) 4478 (26.7)
25–34 3570 (33.6) 3385 (32.9) 5739 (34.4) 6018 (35.9)
35–49 3704 (34.9) 3852 (37.5) 6273 (37.6) 6290 (37.5)
Educational level
No education 4238 (39.5) 3384 (32.9) 4486 (26.8) 4089 (24.4)
Primary 3155 (29.4) 3052 (29.7) 5010 (29.9) 4918 (29.3)
Secondary 2698 (25.1) 3032 (29.5) 5902 (35.2) 6194 (36.9)
Higher 640 (6.0) 807 (7.9) 1365 (8.1) 1585 (9.4)
Number of members in a household
1–2 392 (3.7) 418 (4.1) 710 (4.2) 845 (5.0)
3–4 3132 (29.2) 3201 (31.1) 5781 (34.5) 6280 (37.4)
5+ 7207 (67.2) 6659 (64.8) 10272 (61.3) 9661 (57.6)
Wealth index
Poorest 1930 (18.0) 1658 (16.1) 2887 (17.2) 3023 (18.0)
Poorer 1932 (18.0) 1851 (18.0) 3098 (18.5) 3140 (18.7)
Middle 2004 (18.7) 1934 (18.8) 3221 (19.2) 3410 (20.3)
Richer 2138 (19.9) 2071 (20.1) 3570 (21.3) 3559 (21.2)
Richest 2727 (25.4) 2764 (26.9) 3987 (23.8) 3654 (21.8)
Involved in paid work
No 8302 (77.4) 7178 (69.9) 14467 (86.3) 11338 (67.6)
Yes 2428 (22.6) 3096 (30.1) 2296 (13.7) 5443 (32.4)
Place of residence
Urban 3676 (34.3) 3910 (38.0) 5872 (35.0) 5831 (34.7)
Rural 7055 (65.7) 6368 (62.0) 10891 (65.0) 10955 (65.3)
Region
Barisal 1282 (11.0) 1346 (13.1) 1931 (11.5) 2006 (12.0)
Chittagong 1915 (17.8) 1801 (17.5) 2689 (16.0) 2675 (15.9)
Dhaka 2433 (22.7) 2203 (21.4) 2895 (17.3) 2920 (17.4)
Khulna 1612 (15.0) 1615 (15.7) 2537 (15.1) 2470 (14.7)
Rajshahi 2427 (22.6) 1955 (19.0) 2471 (14.7) 2399 (14.3)
Sylhet 1062 (9.9) 1358 (13.2) 2342 (14.0) 2409 (14.4)
Rangpur - - 1898 (11.3) 1907 (11.4)
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Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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overweight, the increase in obesity between 2011 and 2014 was four times that seen in the pre-
vious four years.
Overall BMI distributions of women are shown in “Fig 2”. The mean (SE) BMI increased
from 20.31(0.03) in 2004 to 22.31 (0.03) in 2014 (p<0.001). The BMI distribution showed a
Fig 1. Trend of overweight and obesity 2004 to 2014.
https://doi.org/10.1371/journal.pone.0181080.g001
Fig 2. BMI distribution of women from 2004 to 2014 (mean and SD).
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Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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clear shift to the right, indicating a nutritional transition from underweight to overweight
(“Fig 2”).
When the data were stratified by age and place of residence it was noted that in all the four
surveys the prevalence of overweight and obesity was less in younger (15 to 24 years) women
compared to older women (25 to 49 years) and less in the rural areas compared to the urban
areas Figs “3” and “4”. For example, in urban Bangladesh in 2014, 10.8% of 15 to 24 year olds
and 23.3% of 35 to 49 year olds were overweight. In the same year, 3.5% of 15 to 24 year olds
and 14.0% of 25 to 49 year olds were obese. In comparison in 2014 in rural Bangladesh 5.0% of
15 to 24 year olds and 12.6% of 35 to 49 year olds were overweight and 0.8% of 15 to 24 year
olds and 25% of 35 to 49 year olds were obese
The PORs for overweight and obesity for women living in urban areas compared with their
rural counterparts, stratified by age are shown in Table 2. In 2004, urban women aged 25 to 34
years were four times more likely [POR 2.8:95% CI: 2.2 to 3.5] to be overweight compared to
women of the same age livening in rural areas. In 2014, the difference between women living
in urban areas compared to rural areas decreased and urban women were twice [OR 1.6:95%
CI 1.4 to 1.9] as likely to be overweight. Similarly for obesity, in 2004 urban women aged 25 to
34 years were four times more likely [OR 3.8:95% CI: 2.5 to 5.6] to be obese. In 2014, urban
women aged 25 to 34 years were three times more likely [OR 3.0:95% CI: 2.4 to 3.7] to be
obese compared to rural women.
The highest prevalence of overweight in women of reproductive age between 2004 and
2014 was consistently seen in those with the highest education level (19.0% in 2004 and 26.4%
in 2014 for urban women and 4.8% in 2004 and 11.2% in 2014 for rural women) and the
Fig 3. Age specific prevalence of overweight and obesity in urban area.
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Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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richest (15.1% in 2004 and 28.59% in 2014% for urban women and 6.2% in 2004 and 20.8% in
2014 for rural women), Table 3.
Women who were not in paid employment also tended to have a higher prevalence of over-
weight. The prevalence of obesity showed a similar pattern to overweight and was highest in
those who had the highest education and the richest, Table 4. The largest increase in the preva-
lence of overweight and obesity was seen in rural women.
Fig 4. Age specific prevalence of overweight and obesity in rural area.
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Table 2. Age specific prevalence odds ratios (POR) with 95% CI associated with overweight and obesity in women living in urban areas compared
with women living in rural areas between 2004 and 2014.
Age group 2004 2007 2011 2014
Overweight POR Lower Upper POR Lower Upper POR Lower Upper POR Lower Upper
15–24 2.3 1.7 3.1 2.0 1.4 2.7 1.9 1.6 2.3 1.6 1.3 2.0
25–34 2.8 2.2 3.5 2.1 1.7 2.6 2.0 1.7 2.4 1.6 1.4 1.9
35–49 2.1 1.6 2.8 2.6 2.1 3.2 2.0 1.7 2.4 1.4 1.2 1.7
Obesity
15–24 4.3 2.3 8.0 3.8 2.2 6.8 2.9 2.0 4.2 2.3 1.6 3.3
25–34 3.8 2.5 5.6 4.0 2.8 5.7 3.2 2.4 4.1 3.0 2.4 3.7
35–49 6.4 4.3 9.6 5.0 3.5 7.2 4.2 3.3 5.4 3.4 2.6 4.4
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Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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Discussion
We found that the prevalence of overweight and obesity among women of reproductive age in
Bangladesh increased by over 2.2 times for overweight, from 11.4% in 2004 to 25.2% in 2014
and 3.2 times for obesity, from 3.5 in 2004 to 11,2% in 2014. Of particular note was that the
rate of increase appears to be accelerating overtime potentially indicating that Bangladeshi
women are on a trajectory to higher levels. The high and increasing proportion of overweight
and obesity that we report threatens the substantial gains that have been made in maternal and
infant health in Bangladesh over the last two decades. Overweight and obesity in women dur-
ing pre-pregnancy or early pregnancy, living in low and middle income countries, has been
associated with increased morbidity in the mother, including hypertension, pre-eclampsia and
diabetes, more complicated deliveries, post-partum haemorrhage and fetal morbidity and
mortality[18]. In India, a neighbouring country with similar rates of overweight and obesity
(25% in women >20 years) [6]the burden of overweight and obesity before and/or during
pregnancy on health is considered to be greater than under nutrition[19].
The proportion of overweight and obese women in Bangladesh that we report is only
slightly lower than that reported in all women living in the South East Region (28% in 2013)
Table 3. Place of residence specific prevalence of overweight between 2004 to 2014.
Variables 2004 2007 2011 2014
Urban Rural Urban Rural Urban Rural Urban Rural
Highest educational level
No education 11.8 (9.2–14.9) 7.6 (6.5–8.8) 14.4 (11.9–17.3) 9.0 (7.6–10.5) 23 (19.9–26.4) 13.0 (11.6–14.5) 25.0 (21.3–29.1) 18.3 (16.3–20.6)
Primary 14.6 (12.2–17.4) 9.3 (7.7–11.2) 20.6 (17.7–23.8) 11.7 (10–13.6) 23.7 (20.6–27.1) 15.3 (13.7–17.0) 28.0 (24.8–31.5) 21.9 (20.2–23.7)
Secondary 24.7 (21.7–27.9) 10.9 (9.1–12.8) 26.4 (23.4–29.6) 13.6 (11.7–15.8) 29.2 (26.6–31.9) 18.4 (16.9–20.1) 32.0 (29.3–34.9) 25.9 (24.1–27.9)
Higher 38.8 (33.4–44.5) 17.2 (12.6–23) 39.2 (34.7–44.0) 27.4 (21.9–33.6) 38.1 (34.0–42.5) 30.6 (26.2–35.5) 42.1 (37.6–46.9) 30.8 (26.2–35.8)
P value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Number of members in a household
1–2 18.5 (12.5–26.7) 11.7 (7.8–17.2) 20.1 (13.6–28.5) 14.3 (10.2–19.8) 28.2 (22.2–35.1) 18.8 (15.0–23.3) 28.4 (23–34.5) 24.7 (20.1–30.0)
3–4 18.3 (15.5–21.5) 9.0 (7.6–10.6) 22.4 (19.4–25.7) 11.8 (10.2–13.6) 28.2 (25.8–30.7) 16.2 (14.7–17.8) 32.1 (29.5–34.9) 24.6 (22.5–26.8)
5+ 19.8 (17.0–22.8) 9.0 (8.0–10.2) 24.3 (21.6–27.2) 11.6 (10.2–13.1) 27.6 (25.2–30.1) 16.1 (14.8–17.5) 30.7 (28–33.5) 21.6 (20.1–23.2)
P value 0.68 0.39 0.44 0.49 0.92 0.42 0.42 0.03
Paid work
No 20.2 (17.7–22.9) 9.6 (8.5–10.8) 25.5 (23.4–27.7) 12.7 (11.4–14.2) 28.9 (26.7–31.1) 15.9 (14.7–17.2) 32.2 (30.2–34.2) 23.2 (21.8–24.8)
Yes 16.7 (13.6–20.4) 7.4 (6.0–9.2) 18.9 (15.8–22.5) 9.9 (8.3–11.7) 24.0 (21–27.4) 19.1 (16.6–21.8) 29.0 (25.2–33) 22.1 (20.1–24.1)
P value 0.06 0.03 0.00 0.01 0.01 0.02 0.09 0.27
Wealth index
Poorest 4.5 (2.5–7.9) 4.4 (3.3–5.8) 4.2 (2.0–8.6) 5.4 (4.3–6.8) 10.2 (7–14.6) 7.9 (6.7–9.2) 13.6 (9.3–19.5) 12.7 (10.7–15)
Poorer 3.9 (2.3–6.6) 4.3 (3.2–5.7) 6.3 (4.0–9.8) 8.5 (6.9–10.4) 16.4 (11.8–22.2) 11.4 (10–12.8) 19.2 (14.9–24.5) 18.3 (16.4–20.4)
Middle 13.1 (9.8–17.4) 8.6 (7–10.5) 10.1 (6.7–15) 10.1 (8.5–12.1) 18.5 (14.5–23.4) 16.9 (15.2–18.8) 28.4 (23.2–34.2) 23.8 (21.7–26.0)
Richer 11.5 (8.6–15.3) 14.6 (12.5–16.9) 19 (15.8–22.6) 16.4 (14.3–18.6) 24.2 (21.7–27) 24.1 (22.1–26.2) 27.4 (24.3–30.8) 33.0 (29.6–36.5)
Richest 28.9 (26.3–31.6) 20.4 (17.2–23.9) 31 (28.7–33.3) 29.1 (24.8–33.7) 33.9 (31.3–36.4) 32.5 (29.4–35.7) 37.4 (34.6–40.2) 36.7 (32.5–41.2)
P value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Region
Barisal 21.0 (11.9–34.4) 6.9 (5.1–9.3) 19.0 (14.3–25) 9.6 (7–13.1) 30.4 (25.8–35.3) 13.5 (11.2–16.2) 31.9 (29–34.9) 17.5 (14.9–20.3)
Chittagong 19.8 (15.8–24.6) 9.3 (7.5–11.5) 21.5 (17.8–25.8) 11.2 (8.6–14.3) 24.8 (21.1–29.0) 19.3 (16.7–22.1) 30.7 (26.4–35.3) 25.2 (21.8–29.1)
Dhaka 20.2 (16.1–25) 9.8 (7.5–12.7) 24.8 (21.4–28.5) 10.2 (8.3–12.5) 28.8 (25.6–32.3) 13.1 (10.6–16.1) 31.6 (27.7–35.8) 23.1 (20.1–26.4)
Khulna 20.1 (16.3–24.6) 11.1 (8.9–13.8) 23.8 (18.7–29.6) 16.6 (14–19.6) 29.4 (24.3–35.1) 21.9 (19.4–24.5) 34.6 (28.9–40.7) 27.2 (24.7–29.8)
Rajshahi 14.5 (10.8–19.2) 8.4 (6.8–10.4) 24.0 (20.1–28.4) 12 (9.7–14.7) 27.7 (24.6–31.0) 18.9 (16.3–21.7) 31.8 (27.7–36.2) 25.2 (22.3–28.5)
Sylhet 20.1 (12.5–30.7) 7.5 (4.9–11.3) 19.0 (14.8–24) 10.8 (7.2–16) 25.1 (20.2–30.8) 12.8 (10.7–15.1) 28.9 (25.1–33) 19 (16–22.5)
Rangpur - - - - 26.5 (22.1–31.5) 11.8 (9.6–14.5) 22.4 (17.6–27.9) 16.7 (14.2–19.5)
P value 0.52 0.29 0.44 0.02 0.42 0.00 0.25 0.00
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Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
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[20], despite being one of the poorest countries in the Region. The trend in the increasing
prevalence is also consistent with the increasing trend in developing countries and while the
prevalence of overweight and obesity tends to be lower in developing countries compared to
developed counties, because of the high population of the area, it is estimated where almost
70% of the world’s obese live[6].
Age, higher education and wealth, as well as living in urban areas were factors associated
with increased overweight and obesity. Our data indicates that women in successive cohorts
are gaining weight at all ages; however the greatest gain was seen in the older age group (35 to
49 years). Previous studies in developing countries have indicated that the highest prevalence
of obesity was seen in women in their mid-fifties[21], indicating that the proportion of Bangla-
deshi women may be higher than what we are reporting in women of reproductive age (15 to
49 years). Another study using the 2011 BDHS data also reported that unemployed urban
women at higher risk of being overweight or obese than those women who were involved in
manual-labored work[22].
The observation that there was an increased proportion of overweight and obesity in
women with a higher socio-economic status in low to middle-income countries, including
Table 4. Place of residence specific prevalence of obesity between 2004 to 2014.
Variables 2004 2007 2011 2014
Urban Rural Urban Rural Urban Rural Urban Rural
Highest educational level
No education 3.7 (2.5–5.4) 0.8 (0.5–1.3) 6.1 (4.3–8.6) 1.9 (1.3–2.6) 11.0 (8.6–14) 3.5 (2.8–4.3) 13.5 (10.8–16.8) 5.1 (4.1–6.4)
Primary 7.1 (5.4–9.3) 2.2 (1.6–3) 9.8 (7.7–12.4) 2.8 (1.9–4) 11.2 (8.9–14) 4.1 (3.3–4.9) 15 (12.6–17.7) 7.3 (6.1–8.8)
Secondary 12.8 (9.8–16.6) 3.5 (2.5–4.7) 14.8 (12.1–18) 4.4 (3.3–5.8) 17 (14.6–19.8) 6.2 (5.3–7.3) 24.3 (21.1–27.8) 9.5 (8.2–11)
Higher 19 (14.4–24.5) 4.8 (2.3–9.5) 23.4 (18.6–29.1) 6.7 (4–11) 22.4 (18.6–26.6) 8.6 (6.3–11.8) 26.4 (23.1–30.1) 11.2 (8.5–14.5)
P value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Number of members in a household
1–2 5.6 (2.7–11.1) 2.2 (0.9–5.4) 13.5 (7.9–22.1) 1.6 (0.6–4.5) 9.7 (6.2–14.8) 7.5 (5.2–10.6) 14 (9.9–19.4) 9.6 (6.8–13.3)
3–4 9.3 (7.1–12) 1.9 (1.3–3) 13.9 (11.1–17.1) 3.9 (3–5.1) 14.7 (12.4–17.3) 5.3 (4.5–6.3) 20.7 (18.1–23.6) 8.3 (7.2–9.6)
5+ 9 (7.2–11.3) 1.9 (1.5–2.4) 11.6 (9.7–13.7) 2.7 (2–3.5) 15.9 (13.6–18.5) 4.3 (3.7–5) 20.2 (17.7–23) 7.2 (6.1–8.4)
P value 0.37 0.96 0.28 0.03 0.07 0.00 0.09 0.10
Paid work
No 10.5 (8.6–12.9) 2.1 (1.6–2.6) 14.9 (12.7–17.4) 3.2 (2.5–4.1) 16.4 (14.2–18.8) 4.8 (4.2–5.4) 22.9 (20.3–25.7) 8.3 (7.1–9.6)
Yes 4.3 (3–6) 1.5 (1–2.4) 6.6 (4.8–9) 2.7 (1.9–4) 10.3 (8.5–12.5) 4.7 (3.5–6.4) 14.1 (11.8–16.8) 6.7 (5.6–7.9)
P value 0.00 0.17 0.00 0.47 0.00 0.96 0.00 0.02
Wealth index
Poorest 0.8 (0.2–3.4) 0.3 (0.1–0.7) 2.5 (0.9–6.8) 0.8 (0.4–1.5) 1.1 (0.4–2.7) 1.7 (1.2–2.3) 4.6 (2.7–7.8) 2.4 (1.8–3.3)
Poorer 1.9 (0.8–4.2) 1 (0.6–1.9) 1.8 (0.8–4.2) 0.9 (0.5–1.7) 2.1 (1–4.3) 2.1 (1.5–2.7) 5.4 (3.4–8.4) 4.8 (3.7–6.2)
Middle 1.7 (0.8–3.5) 1.4 (0.9–2.2) 2.8 (1.5–5.2) 2.9 (2–4) 4.4 (2.9–6.9) 4.1 (3.3–5.1) 10.3 (7.7–13.9) 7.3 (5.9–9)
Richer 4.3 (2.6–7) 3.3 (2.2–4.8) 6 (4.2–8.7) 4.5 (3.2–6.2) 9 (7.2–11.1) 8.1 (6.9–9.4) 15.2 (12.9–17.8) 12 (10.5–13.7)
Richest 15.1 (12.8–17.7) 6.2 (4.3–8.7) 18.2 (15.9–20.7) 10.9 (8.1–14.5) 22.2 (19.8–24.8) 14.8 (12.4–17.5) 28.5 (26.1–31) 20.8 (16.9–25.2)
p value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Region
Barisal 10.2 (6.8–14.9) 2.2 (1.4–3.5) 7.3 (4.8–11) 1.8 (1.1–2.9) 13.4 (9.9–17.9) 3.2 (2.2–4.5) 25 (17.9–33.8) 5.5 (4.3–7)
Chittagong 7.6 (4.8–11.8) 2.5 (1.7–3.8) 12.7 (9.5–16.7) 3.5 (2.3–5.5) 13.3 (10.4–16.8) 7.2 (5.6–9.1) 21.4 (17.1–26.5) 9.3 (7.7–11)
Dhaka 10.3 (7.3–14.2) 2 (1.2–3.4) 13.5 (10.5–17.2) 3.5 (2–6) 16.6 (13.3–20.5) 3.6 (2.6–5) 20.3 (16.7–24.5) 7.8 (5.4–11.1)
Khulna 11.5 (7.7–16.8) 1.6 (1–2.7) 8.4 (5.2–13.1) 3.2 (2–5) 15.7 (12.9–18.8) 6.4 (5.3–7.7) 18.8 (16–22.1) 11.5 (9.6–13.7)
Rajshahi 5 (3–8.4) 1.6 (1–2.7) 13.6 (9.8–18.6) 2.7 (1.9–4) 13.4 (10–17.8) 4.6 (3.4–6.1) 17.5 (13.9–21.8) 6.9 (5.4–8.8)
Sylhet 7.9 (5.6–11.1) 2 (1.2–3.6) 8.3 (4.6–14.3) 2.1 (1.1–4) 10.3 (7–15.1) 3.5 (2.5–4.8) 18.8 (14.1–24.7) 5.7 (4.5–7.3)
Rangpur 15.3 (11.4–20.2) 4.2 (2.7–6.4) 13.8 (9.9–18.8) 5.2 (4.1–6.5)
P value 0.10 0.69 0.18 0.59 0.21 0.00 0.34 0.01
https://doi.org/10.1371/journal.pone.0181080.t004
Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
PLOS ONE | https://doi.org/10.1371/journal.pone.0181080 July 28, 2017 9 / 12
India, Iran and Vietnam, has also been consistently reported[23–31]. In China, an increase in
income has been associated with an increase intake of energy and fat, and consumption of ani-
mal and processed foods, all of which are associated with overweight and obesity [32]. We
speculate that the association between higher education and wealth and overweight and obe-
sity, in addition to potential dietary differences is due to the nature of the work that the
women may undertake; educated women are more likely to engage in jobs that involve less
physical activity. A lower prevalence of overweight and obesity were reported in women who
are unemployed compared to those who were involved in manual labour [20]. However, in
contrast a study in the north-west Iran demonstrated that higher education was negatively cor-
related with obesity in women, a pattern which is consistent with that observed in high-income
countries [28].
This is the first study to examine the trends in the prevalence of overweight and obesity in
Bangladeshi women of reproductive age. This is important information for national health
policy maker to take initiative to prevent upcoming public health burden. The strength of this
study is that it is analysis of large national samples consisting of women living in both urban
and rural areas in Bangladesh. However, there are a number of limitations. The surveys are
cross-sectional and the analyses presented are associations and causality between nutritional
status and determinants cannot be elucidated. In addition, the BDHS data did not include
information on dietary habits or physical activity and hence major determinants of nutritional
status were not explored.
Conclusion
We assessed the prevalence of overweight and obesity among Bangladeshi women of repro-
ductive age using a decade of data. The increase in the prevalence of overweight and obesity
was especially significant in older, higher educated women with increased wealth. Our study
also indicated that the burden of overweight and obesity among women of reproductive age is
high and continuing to increase over time. Overweight and obesity in reproductive age are
associated with poor reproductive outcomes of women and increased risk of non-communica-
ble diseases and therefore, demands attention from public health program authorities for con-
tinuous success in women and child health indicators.
Acknowledgments
The data used in this study were obtained from the open access dataset of BDHS. The authors
acknowledge the contributions of the BDHS team for their efforts in providing open access to
the dataset. We thank Mr. Saimul Islam for supporting the data analysis. icddr,b is thankful to
the Government of Bangladesh, Canada, Sweden and the UK for providing core support.
Author Contributions
Conceptualization: Tuhin Biswas, Sarah P Garnett.
Data curation: Tuhin Biswas.
Formal analysis: Tuhin Biswas, Sarah P Garnett.
Methodology: Tuhin Biswas, Sonia Pervin, Sarah P Garnett.
Supervision: Md. Jasim Uddin, Abdullah Al Mamun, Sarah P Garnett.
Writing – original draft: Tuhin Biswas.
Increasing prevalence of overweight and obesity in Bangladeshi women of reproductive age
PLOS ONE | https://doi.org/10.1371/journal.pone.0181080 July 28, 2017 10 / 12
Writing – review & editing: Tuhin Biswas, Md. Jasim Uddin, Abdullah Al Mamun, Sonia Per-
vin, Sarah P Garnett.
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