Weight trajectory during the COVID-19 pandemic: A cross-sectional study in Malaysia - De Gruyter
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Open Health 2022; 3: 44-49
Research Article
Seok Tyug Tan*, Seok Shin Tan, Chin Xuan Tan
Weight trajectory during the COVID-19 pandemic:
A cross-sectional study in Malaysia
https://doi.org/10.1515/openhe-2022-0006
received December 01, 2021; accepted March 11, 2022
1 Introduction
The number of coronavirus disease confirmed cases in
Abstract: This study examines the weight trajectory of
Malaysia (referred to as COVID-19) continued to rise, even
Malaysian adults and its associated factors during the
though three nationwide lockdowns (also known as Move-
COVID-19 pandemic. Sociodemographic information and
ment Control Order, MCO) had been executed. During
anthropometric measurements, including body height
the enforcement of the MCOs, non-essential industries,
(cm) and body weights (kg) before and during the pan-
learning institutions, fitness centers, and recreational
demic, were self-reported by the respondents. The current
parks were instructed to close temporarily because of
study showed that 47.8% (using absolute weight change
difficulty in practicing physical distancing [1]. Restricted
status) and 25.5% (using relative weight change status) of
movement, unhealthy dietary patterns, and a reduction in
the adults gained weight during the COVID-19 pandemic.
moderate-to-vigorous intensity physical activity related to
Adults who were previously underweight or had a normal
limited access to exercise amenities during the MCO can
BMI experienced significantly higher body weight (under-
significantly impact body weight status [2–4].
weight: t= -6.176, p< 0.001 and normal: t= -6.193, p< 0.001)
Based on the recent National Health and Morbidity
and BMI (underweight: t= -6.127, p< 0.001 and normal:
Survey 2019 [5], 1 in 2 adults in Malaysia are currently
t= -5.982, p< 0.001) during the pandemic. No significant
obese or overweight. The implementation of the MCO may
associations were observed between socio-demographic
have worsened the obesity epidemic in Malaysia as a result
characteristics and the weight status of the respondents,
of its imposing sudden lifestyle changes. To the best of the
except for ethnicity (χ2= 12.858, p= 0.045). The stay-at-
authors’ knowledge, only a few studies have investigated
home orders appeared to drive up the prevalence of over-
the impact of COVID-19 lockdown on the body weight
weight/obesity, BMI, and absolute and relative weight
status of various populations. The findings from China [6],
gain in Malaysian adults. The increase was mainly asso-
Italy [7], Malaysia [8], and Saudi Arabia [9] suggest that
ciated with higher body weight and BMI among those pre-
the pandemic caused an increase in obesity rates. Because
viously underweight or had a normal BMI. Gender, age,
obesity is positively correlated with impaired metabolic
marital status, and educational level were not associated
health and the onset of non-communicable diseases [10],
with weight trajectory during the COVID-19 pandemic. The
this study examines the weight trajectory and its associ-
findings of this study may be useful in formulating weight
ated factors among adults during the pandemic.
management strategies in the post-pandemic era.
Keywords: Weight trajectory, socio-demographic, adults,
COVID-19, Malaysia
2 Methods
*Corresponding author: Seok Tyug Tan, Department of Healthcare This online cross-sectional study involved 1346 Malay-
Professional, Faculty of Health and Life Sciences, Management and sian adults. Data collection was conducted from March 15
Science University, University Drive, off Persiaran Olahraga, Seksyen to June 1, 2021 (a year after the declaration of Movement
13, 40100 Shah Alam, Selangor, Malaysia
Control Order 1.0) using convenience and snowball sam-
Tel.: +603-5521 6461, Email: sttan@msu.edu.my
Seok Shin Tan, Jeffrey Cheah School of Medicine and Health Scien- pling techniques [11]. An anonymous self-administered
ces, Monash University Malaysia, Bandar Sunway, 47500 Selangor, questionnaire was hosted on a Google Form and circu-
Malaysia lated to the prospective respondents through social media
Chin Xuan Tan, Department of Allied Health Sciences, Faculty of Sci- platforms, including WhatsApp, Telegram, Facebook, and
ence, Universiti Tunku Abdul Rahman, Jalan Universiti, Bandar Barat,
TikTok. Those who responded to the initial request were
31900 Kampar, Perak, Malaysia
Open Access. © 2022 Seok Tyug Tan et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 In-
ternational License.Weight trajectory during the COVID-19 pandemic: A cross-sectional study in Malaysia 45
encouraged to share the survey link with someone else 4 Results
they knew. Individuals aged 18–64 years, free from obe-
sity-associated comorbidities, holding Malaysian citizen- Table 1 shows the socio-demographic characteristics
ship, having access to the internet, and not participating and body weight status of the respondents. The majority
in weight management programs during the pandemic were females (69.2%), aged 20–29 years (76.3%), Malay
were included in this study. (59.0%), single marital status (76.4%), and tertiary-edu-
Sociodemographic information and anthropometric cated (63.6%). In terms of the body weight status, 37.0%
measurements, including body height (cm), pre-pandemic and 38.0% of the respondents had a normal BMI before
body weight (kg), and current body weight (body weight and during the pandemic, respectively. There was a sig-
during the pandemic) (kg), were self-reported by the nificantly higher mean BMI during the pandemic (24.02
respondents [4]. The Body Mass Index (BMI) (kg/m2) was ± 5.50 kg/m2) compared to pre-pandemic (23.91 ± 5.57
computed based on Asia-Pacific cutoff points suggested kg/m2) (t= -1.980, p= 0.048). It is also worth highlighting
by World Health Organization [12]. The weight trajectory that an average absolute weight gain of 3.98 ± 3.25 kg was
during the pandemic was expressed as absolute weight observed among 47.8% of the respondents, whereas 35.2%
change (kg) and relative weight change (%). The absolute reported an absolute weight loss of 4.67 ± 3.87 kg during
weight change was calculated using Formula 1 and further the pandemic. In reference to relative weight change, a
stratified into weight loss (< 0 kg), sustained weight (0 kg), large proportion of the respondents (39.3%) maintained
and weight gain (> 0 kg). Additionally, Formula 2 was used a fairly stable body weight (a slight rise by 1.73%) after a
to quantify the relative weight change of the respondents, year of the COVID-19 pandemic. Slightly more than one-
which was then ranked into three categories: weight loss third (35.2%) lost weight during the pandemic, with a rel-
(≤ -5%), sustained weight (± 4.99%), and weight gain (≥ ative weight loss of 6.65 ± 4.62%. On the contrary, those
+5%) [13]. that gained weight during the pandemic (25.5%) reported
a relative weight gain of 9.61 ± 5.21% compared to their
pre-pandemic weight.
Formula 1: Table 2 shows the trajectories of body weight and BMI
in relation to pre-pandemic BMI status. The findings of
Absolute weight change (kg) = Current body weight – current study revealed that respondents who were under-
Pre pandemic body weight weight or had a normal BMI gained significantly higher
body weight (underweight: t= -6.176, p< 0.001 and normal:
t= -6.193, p< 0.001) and BMI (underweight: t= -6.127, p<
Formula 2: 0.001 and normal: t= -5.982, p< 0.001) after a year of COVID-
19 outbreak in Malaysia. Paradoxically, respondents who
were obese had a significantly lower body weight (t= 3.146,
p= 0.002) and BMI (t= 2.988, p= 0.003) during the COVID-
19 pandemic. However, there was no significant difference
in the body weight (t= -0.173, p= 0.863) and BMI (t= -0.164,
p= 0.870) of those who were overweight pre-pandemic.
In addition, no significant associations were observed
3 Data analysis between the socio-demographic characteristics and the
weight status of the respondents, with the exception of
Data analysis was carried out using IBM SPSS statistics ethnicity (χ2= 12.858, p= 0.045) (Table 3). The findings from
26.0 (IBM Corp., Armonk, NY, USA). Socio-demographic One-way ANOVA further indicated that Malaysian Indians
characteristics and anthropometric measurements were had a significantly higher relative weight gain (F= 4.501,
presented as percentage and mean and standard devia- p= 0.004) than other ethnicities (results are not shown in
tion (SD) where applicable. The mean difference in body the table).
weight and BMI were analyzed with a paired-samples
t-test. The association between socio-demographic char-
acteristics and weight trajectory was investigated using
Pearson’s Chi-squared (categorical variables) or Pearson’s
Correlation test (continuous variables). A p-value of less
than 0.05 (p< 0.05) was considered statistically significant.46 Seok Tyug Tan et al.
Table 1: Socio-demographic characteristics and weight status of the respondents.
Variable Frequency, n (%) Mean ± standard deviation
Gender
Male 420 (30.8) –
Female 944 (69.2)
Age (years old)
< 20 58 (4.3)
20-29 1041 (76.3) 25.00 ± 5.39
30-39 242 (17.7)
≥ 40 23 (1.7)
Ethnicity
Malay 805 (59.0)
Chinese 232 (17.0) –
Indian 296 (21.7)
Others (Bumiputra of Sabah and Sarawak) 31 (2.3)
Marital Status
Single 1042 (76.4) –
Married 322 (23.6)
Educational level
No formal/primary 46 (3.4)
Secondary 451 (33.1) –
Tertiary 867 (63.6)
BMI status (kg/m2)
Pre-pandemic
Underweight 201 (14.7)
Normal 504 (37.0) 23.91 ± 5.57a
Overweight 204 (15.0)
Obese 455 (33.4)
During the pandemic
Underweight 175 (12.8)
Normal 518 (38.0) 24.02 ± 5.50b
Overweight 197 (14.4)
Obese 474 (34.8)
Absolute weight change (kg)
Sustained weight 232 (17.0) –
Weight loss 480 (35.2) -4.67 ± 3.87
Weight gain 652 (47.8) 3.98 ± 3.25
Relative weight change (%)
Sustained weight 536 (39.3) 1.73 ± 1.72
Weight loss 480 (35.2) -6.65 ± 4.62
Weight gain 348 (25.5) 9.61 ± 5.21
Mean difference was analyzed with paired samples t-test. a,b Different letters indicates a significant difference at p< 0.05.
5 Discussion Coincidentally, findings in the current study also revealed
a marginal increase (pre-pandemic – 48.4% versus during
the pandemic – 49.2%) in the prevalence of overweight/
Recent literature has consistently demonstrated that
obese among the Malaysian adults after a year into the
COVID-19 lockdown worsened the global obesity epidemic
COVID-19 pandemic.
[14, 15]. A recent study by Tan, Tan, & Tan [4], for instance,
A few studies have suggested that a weight fluctuation
pointed out that the prevalence of overweight/obesity
of less than 5% from the pre-pandemic body weight is neg-
among Malaysian university students increased from
ligible [13, 16]. Therefore, weight trajectory in the current
34.0% (pre-pandemic) to 34.7% (during the pandemic).
study was expressed in absolute weight change and rel-Weight trajectory during the COVID-19 pandemic: A cross-sectional study in Malaysia 47
Table 2: Trajectories of body weight and Body Mass Index (BMI) in the time of COVID-19.
Pre-pandemic Body weight (kg) t (p-value)1 BMI (kg/m2) t (p-value)1
BMI status (mean ± standard deviation) (mean ± standard deviation)
Pre-pandemic During the Pre-pandemic During the
pandemic pandemic
Underweight 44.91 ± 4.85 46.18 ± 5.78 - 6.176 (48 Seok Tyug Tan et al.
access during the MCO. Second, females were over-repre- Research Ethics Committee of Management and Science
sented in this study, as were those in younger age groups University, Malaysia
and individuals with a higher socio-economic status.
Consequently, findings in the current study cannot be Data availability statement: All data generated or ana-
generalized to all populations in Malaysia. Third, a bias lyzed during this study are included in this published
may have been introduced because individuals who were article
obese prior to the pandemic and/or those who gained a lot
of body weight might not have chosen to participate in this
study. Despite these limitations, this study is the first that
examines the weight trajectory and its associated factors
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