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. 2024 Jan 31;4(1):e0002537. doi: 10.1371/journal.pgph.0002537

Factors associated with overweight and obesity among women of reproductive age in Cambodia: Analysis of Cambodia Demographic and Health Survey 2021–22

Samnang Um 1,2,*, Yom An 1,3
Editor: Abraham D Flaxman4
PMCID: PMC10830042  PMID: 38295032

Abstract

Overweight and obesity are associated with increased chronic disease and death rates globally. In Cambodia, the prevalence of overweight and obesity among women is high and increasing. This study aimed to determine the prevalence and factors associated with overweight and obesity among women of reproductive age (WRA) in Cambodia. We analyzed data from the 2021–22 Cambodia Demographic and Health Survey (CDHS). Data analysis was restricted to non-pregnant women, resulting in an analytic sample of 9,417 WRA. Multiple logistic regressions were performed using STATA V17 to examine factors associated with overweight and obesity. The prevalence of overweight and obesity among WRA was 22.56% and 5.61%, respectively. Factors independently associated with increased odds of overweight and obesity included women aged 20–29 years [AOR = 1.85; 95% CI: 1.22–2.80], 30–39 years [AOR = 3.34; 95% CI: 2.21–5.04], and 40–49 years [AOR = 5.57; 95% CI: 3.76–8.25], women from rich wealth quintile [AOR = 1.44; 95% C: 1.19–1.73], having three children or more [AOR = 1.40; 95% CI: 1.00–1.95], ever drink alcohol [AOR = 1.24; 95% CI: 1.04–1.47], and current drink alcohol [AOR = 1.2; 95% CI: 1.01–1.45]. Women completed at least secondary education were less likely being overweight and obese [AOR = 0.73; 95% CI: 0.58–0.91]. Overweight and obesity remains highly prevalent among WRA in Cambodia. Therefore, there is an urgent need to take interventions that target women from higher socio-demographic status to reduce the risk of life-threatening caused by being overweight and obese through raising awareness of important changing lifestyles.

Introduction

Overweight and obesity are significant global public health challenges that have rapidly risen in the last four decades and are regarded as an epidemic [1]. In 2016, approximately 39% (1.9 billion) of adults aged 18 years and older were overweight, and 13% (650 million) were obese worldwide [1]. Being overweight and obese are major risk factors for several non-communicable diseases (NCDs), including cardiovascular (CVDs), kidney diseases, type 2 diabetes, some cancers, musculoskeletal disorders, and other chronic diseases [2, 3]. Moreover, among women of reproductive age (WRA), overweight and obesity have been associated with increased risk of pregnancy complications, cesarean section births, adverse birth outcomes, and infant mortality [4]. Overweight and obesity are the fourth leading cause of risk-attributable mortality [5], with a reduced life expectancy of 5–20 years, depending on the condition’s severity and comorbidities [1]. According to the WHO, being overweight and obese are the leading risks for global deaths, with at least 2.8 million adults dying annually due to these conditions [1]. Overweight and obesity were higher among women than men in both developed and developing countries. Getahun H. et al. found that overweight was 40% in women vs. 39% in men, and obesity was 15% in women vs. 11% in men [1]. The Global Nutrition Report 2019 showed that 26.1% of women and 20.4% of men were overweight, while obesity was 6.3% in women compared to 3.5% in men [6]. Along with the rapidly increasing population in Cambodia, from 15.42 million in 2015 to nearly 16.21 million in 2019 [7], the prevalence of overweight and obesity is also steadily rising. According to the Cambodia STEPS survey, the overall prevalence of current smoking any tobacco was 29.4% in 2010 to 22.1% in 2016, and current drinking alcohol was 53.5% in 2010 to 46% in 2016, 11% were low physical activity in 2010 to 13% in 2016 [11]. In addition, 63% of women consumed sweet beverages, and 33% consumed unhealthy foods the previous day in 2021–22 [8]. The 2021–22 Cambodia Demographic and Health Survey (CDHS) report indicated that overweight and obesity among non-pregnant women of reproductive age increased from 18% (15.2% overweight and 2.8% obese) in 2014 to 33% (26% overweight and 6% obese) in 2021–22 [8]. It was estimated that overweight and obese contribute to rising healthcare costs in Cambodia (approximately 1.7% of its annual gross domestic product (GDP) per capita) and is a significant contributor to mortality and decreased general health and productivity [9]. Predictors of overweight and obesity among WRA from Demographic and Health Survey (DHS) data such as Cambodia, Bangladesh, Nepal, India, and Ethiopia include higher socioeconomic status, older age, marriage, living in an urban residence, and lack of education [3, 10–12]. Women with formal employment had higher odds of being overweight or obese than informally employed women [3, 13]. Being overweight and obese were more common in women who used hormonal contraceptives such as oral contraceptive pills, implants, patches, and rings [14, 15]. Globally, 30% of daily smokers are overweight or obese [16], with women smokers at greater risk for obesity than men smokers [17, 18]. Women with frequent television watching [19], alcohol drinking [20, 21], and regular consumption of sweets foods and unhealthy foods [22] were found to have higher odds of being overweight or obese. To our knowledge, factors associated with overweight and obesity, specifically among WRA in Cambodia using updated data, have not been explored. A previous study on the prevalence of overweight and obesity among WRA and its associated factors utilized data since 2014 [3]. In Cambodia, where the prevalence of overweight and obesity in WRA has increased rapidly, a comprehensive investigation of a wide range of socio-demographic and behavioral factors is warranted to identify the factors independently associated with having overweight and obesity. Identifying the critical modifiable socio-demographic and behavioral factors, as well as women at a high risk of being overweight and obese, may help guide the timely development of promising and feasible public health intervention strategies to address the growing overweight and obesity pandemic. Therefore, we aimed to determine the prevalence and examined socio-demographic and behavioral factors associated with overweight and obesity among WRA in Cambodia.

Material and methods

Ethics statement

The study data used in this study were women’s data, which were extracted from the most recent CDHS 2021–22 [8], which are publicly available with all personal identifiers of study participants removed. Also, the CDHS data are publicly accessible and were made available to us upon request through the DHS website at (URL: https://dhsprogram.com/data/available-datasets.cfm). Written informed consent was obtained from the parent/guardian of each participant under 18. The data collection tools and procedures for CHDS 2021–22 were approved by the Cambodia National Ethics Committee for Health Research on 10 May 2021 (Ref: 083 NECHR) and the Institutional Review Board (IRB) of ICF in Rockville, Maryland, USA.

Data sources and procedures

We followed the methods of Um S et al., 2023 [3]. To analyze the prevalence and factors associated with overweight and obesity among WRA in Cambodia, we used existing women’s data from the 2021–22 CDHS, which was a nationally representative population-based household survey implemented by the National Institute of Statistics (NIS) in collaboration with the Ministry of Health (MoH). Data was collected from September 15, 2021, to February 15, 2022 [8]. The sampling frame used for the 2021–22 CDHS was taken from the Cambodia General Population Census 2019 [7]. After that, the participants were selected using probability proportion based on two-stage stratified cluster sampling from the chosen sampling frame. In the initial stage, 709 enumeration areas (EAs) (241 urban areas and 468 rural areas) were selected. In the second stage, an equal systematic sample of 25–30 households was selected from each cluster of 21,270 households. In total, 19,496 women aged 15–49 were interviewed, with a response rate of 98.2%. Survey data were obtained through face-to-face interviews using a standardized survey instrument by trained interviewers. Anthropometric weight and height measurements for adult women aged 15–49 were taken by trained female field staff using standardized instruments and procedures [7]. Weight measurements were taken using scales with a digital display (UNICEF model S0141025). Height was measured using a portable adult height measurement system (UNICEF model S0114540). The detailed protocol and methods were published previously [8]. Eligible participants for this study were women of reproductive age 15–49 years, with the exclusion of pregnant women and those who had a birth within two months before the survey, with available body mass index (BMI) data. As a result, we excluded 828 pregnant women and 9,249 women with missing BMI data. A final sample included in this analysis was 9,417 women of reproductive age 15–49 years.

Measurements

Outcome variable

The primary outcome variable of this study was overweight and obese for women of reproductive age. BMI—defined by dividing a person’s weight in kilograms by the square of their height in meters (kg/m2)–was used to measure the outcome [8, 23]. For adults over 15 years old, the following BMI ranges were used: Underweight (≤ 18.4 kg/m2), Normal weight (18.5–24.9 kg/m2), Overweight (25.0–29.9 kg/m2), and Obesity (≥ 30.0 kg/m2) [8, 23]. Overweight/Obese was defined as a binary outcome for which women with a BMI ≥ 25.0 kg/m2 were classified as overweight and obese (coded = 1), while women with a BMI < 25.0 kg/m2 were coded as other (coded = 0).

Independent variables

Independent variables consisted of sociodemographic characteristics and behavioral factors, women’s age in years (15–19, 20–29, 30–39, and 40–49), marital status (not married, married or living together, and divorced or widowed or separated), educational level (no formal education, primary, secondary or higher education), occupation (not working, agriculture, manual labor or unskilled, professional or sealer or services), and number of children ever born (no children, one-two child, and three and more children). Households’ wealth status was represented by a wealth index calculated via principal component analysis (PCA) and using variables for household assets and dwelling characteristics. Weighted scores are divided into five wealth quintiles (poorest, poorer, medium, richer, and richest), each comprising 20% of the population [8] and place of residence (rural vs. urban). Cambodia’s provinces were regrouped for analytic purposes into a categorical variable with four geographical regions: plains, Tonle Sap, coastal/sea, and mountains [7]. Behavioral factors included smoking (non-smoker vs. smoker), alcohol consumption in the past month (never drink, ever drink, and current drink), current alcohol drinking corresponded to one can or bottle of beer, one glass of wine, or one shot of spirits in the past month, watching television at least once a week (yes vs. no), contraceptive usage (not used, hormonal methods (using a pill, emergency contraceptive pill, Norplant, injection, and vaginal rings), non-hormonal methods (condoms, the diaphragm, the IUD, spermicides, lactational amenorrhea, and sterilization), and traditional methods (periodic abstinence and withdrawal) [8].

Statistical analysis

Statistical analyses were performed using STATA version 17 (Stata Corp 2021, College Station, TX) [24]. We accounted for CDHS sampling weight and complex survey design using the survey package in our descriptive and logistic regression analyses. Key socio-demographic characteristics and behavioral factors were described in weighted frequency and percentage. The provincial variation in the prevalence of overweight and obesity was done using ArcGIS software version 10.8 [24]. A shapefile for Cambodian administrative boundaries was obtained from the United Nations for Coordination of Humanitarian Affairs (OCHA) https://data.humdata.org/dataset/cod-ab-khm?. License (https://data.humdata.org/faqs/licenses).

Bivariate analysis using Chi-square tests was used to assess associations between independent variables (socio-demographic characteristics and behavioral factors) and Overweight/Obese. Variables associated with overweight and obese at p-value ≤ 0.10 [3] or that had a potential confounder variable (for example, women’s age, household wealth index, alcohol consumption, and place of residence) were included in the final multiple logistic regression analyses. Simple logistic regression was used to determine the magnitude effect of associations between overweight and obesity with socio-demographic characteristics and behavioral factors. Results are reported as odds ratios (OR) with 95% confidence intervals (CI). Multiple logistics regression was then used to assess independent factors associated with overweight and obesity after adjusting for other potential confounding factors in the model. Results from the final adjusted model are reported as adjusted odds ratios (AOR) with 95% CI and corresponding p-values. Multicollinearity between independent variables was checked before fitting the final regression model, including women’s age, number of children ever born, education, household wealth index, occupation, marital status, place of residence, and geographical regions. The result of the evaluation of variance inflation factor (VIF) scores after fitting an Ordinary Least Squares regression model with the mean = 1.44 indicated no collinearity concerns [25] (see S1 Table).

Results

Characteristics of the study samples

The mean age of women was 31 years old (SD = 9.6 years), of which the 30–49 age group accounted for 57.11%. Almost 67.82% were married, 49.47% had completed at least secondary education, and 11.90% did not receive formal schooling. 30.30% of women did professional work, and 25.86% were unemployed. Of the total sample, 35.97% of women were from poor households. Over half (57.27%) of women resided in rural areas. About 27.79% had three or more children, while 29.49% had no children. Only 1.40% of women reported cigarette smoking, 16.60% reported currently drinking alcohol, 18.6% reported ever drinking, and 12.35% reported using hormonal contraceptives. The mean women’s BMI was 22.9 kg/m2 (SD = 3.9 kg/m2), and 22.56% and 5.61% were overweight and obese, respectively (see Table 1).

Table 1. Socio-demographic and behavior characteristics of the weighted samples of women aged 15–49 years old in Cambodia, 2021–2022 (n  =  9,417, weighted count).

Variables Freq. Percent (95% CI)
Women’s mean age in years (SD) 30.9 (9.6)
15–19 1,488 15.80
20–29 2,551 27.09
30–39 3,220 34.19
40–49 2,158 22.92
Marital status
Not married 2,429 25.79
Married or living together 6,387 67.82
Widowed/divorced/separated 601 6.38
Education
No education  1,121 11.90
Primary  3,637 38.62
Secondary and higher  4,659 49.47
Current work status
Not working 2,435 25.86
Agricultural 1,607 17.06
Professional 2,853 30.30
Manual labor and unskilled 2,331 24.75
Number of children born
No birth 2,777 29.49
1–2 child 4,023 42.72
Three or above 2,617 27.79
Household wealth index
Poor 3,387 35.97
Middle  1,822 19.35
Rich 4,207 44.67
Smoking
Non-smoker 9,285 98.60
Smoker 132 1.40
Current drinking alcohol
Never drink 6103 64.80
Ever drink 1751 18.60
Current drink 1562 16.60
Frequency of watching television
Not at all 5,808 61.68
Less than once a week 1,493 15.85
At least once a week 2,116 22.47
Ever report of contraceptive use
No method 5,152 54.71
Traditional method 2,398 25.46
Non-hormonal method 704 7.48
Hormonal method 1,163 12.35
Place of residence
Urban 4,024 42.73
Rural 5,393 57.27
Region
Plain 4,708 49.99
Tonle Sap 2,859 30.36
Coastal 595 6.32
Plateau/Mountain 1,255 13.33
BMI means in kg/m2 (SD) 22.9 (3.9)
Underweight 1013 10.76 (9.9–11.7)
Normal weight 5751 61.08 (59.7–62.5)
Overweight 2124 22.56 (21.5–23.7)
  Obese 528.2 5.61 (5.0–6.3)
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Notes: Survey weights are applied to obtain weighted percentages. Plains: Phnom Penh, Kampong Cham, Tbong Khmum, Kandal, Prey Veng, Svay Rieng, and Takeo; Tonle Sap: Banteay Meanchey, Kampong Chhnang, Kampong Thom, Pursat, Siem Reap, Battambang, Pailin, and Otdar Meanchey; Coastal/sea: Kampot, Kep, Preah Sihanouk, and Koh Kong; Mountains: Kampong Speu, Kratie, Preah Vihear, Stung Treng, Mondul Kiri, and Ratanak Kiri.

Distribution of overweight and obesity among WRA by provinces

The prevalence of overweight and obesity is highest among WRA in Kampong Cham (34.1%), Kandal (32.3%), Svay Rieng (32%), Preah Sihanouk (31.2%), Phnom Penh, Kompong Thom, Pailin, and Tboung Khmum (30% each) and lowest among WRA in Ratanak Kiri (9.4%) and Kampong Chhnang (14.6%) (see Fig 1, and S2 Table).

Fig 1. Prevalence of overweight and obesity in Women Reproductive Age by province.

Fig 1

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The map was created using ArcGIS software version 10.8 [24]. A shapefile for Cambodian administrative boundaries was obtained from the United Nations for Coordination of Humanitarian Affairs (OCHA) https://data.humdata.org/dataset/cod-ab-khm?. License (https://data.humdata.org/faqs/licenses).

Factors associated with overweight and obesity in bivariate analysis

In bivariate analysis, all socio-demographic characteristics and behavioral factors were significantly associated with overweight and obesity, except smoking status and frequency of watching television (Table 2). Women had a higher prevalence of overweight/obesity if they were aged 40–49 years (47.31%) compared to younger age groups (p-value <0.001), married (35.87%) compared to another relationship status (p-value <0.001), had no formal education (37.91%) compared to higher education (p-value <0.001), were employed in a professional job (34.03%) compared to other careers, or were from the rich households (30.90%) compared to poor households (p-value <0.001). In addition, Overweight/obesity increased with parity. Women reported at least three children had a significantly higher proportion of overweight and obesity (42.53%) compared to those who had children less than three (p-value < 0.001). Women who currently drink alcohol had a significantly higher proportion of overweight and obese (33.87%) than women who did not (p-value <0.001). Women who used hormonal contraceptive methods had a significantly higher proportion of overweight and obesity (37.92%) than women who did not use contraceptives (p-value <0.001). Geographic regions of residence were likewise associated with a woman being overweight and obese. Women who lived in urban areas had a higher prevalence of overweight and obesity than those living in rural areas (29.90% vs 26.87%, p-value = 0.028). Plain regions were positively associated with overweight and obesity (29.91%) compared to the other areas (p-value = 0.006).

Table 2. Factors associated with overweight and obesity among women aged 15–49 years in Chi2 analysis (n  =  9,417, weighted count).

Characteristics Overweight/Obese (n = 2,652) Normal/Underweight (n = 6,764) P value
Freq. % Freq. %
Women’s age group in years
15–19 80 5.38 1,408 94.62 <0.001
20–29 444 17.40 2,107 82.60
30–39 1,108 34.41 2,112 65.59
40–49 1,021 47.31 1,137 52.69
Marital status
Not married 181 7.45 2,248 92.55 <0.001
Married or living together 2,291 35.87 4,096 64.13
Widowed/divorced/separated 181 30.12 420 69.88
Education
No formal education  425 37.91 695 62.00 <0.001
Primary  1,254 34.48 2,383 65.52
Secondary and higher  973 20.88 3,686 79.12
Current work status
Not working 586 24.07 1,849 75.93 <0.001
Agricultural 485 30.18 1,121 69.76
Professional 971 34.03 1,881 65.93
Manual labor and unskilled 563 24.15 1,768 75.85
Number of children born
No birth 264 9.51 2,512 90.46 <0.001
1–2 child 1,275 31.69 2,748 68.31
Three or above 1,113 42.53 1,504 57.47
Household wealth index
Poor 841 24.83 2,546 75.17 <0.001
Middle  512 28.10 1,311 71.95
Rich 1,300 30.90 2,907 69.10
Smoking
Non-smoker 2,621 28.23 6,664 71.77 0.325
Smoker 32 24.24 100 75.76
Current drinking alcohol
Never drink 1,573 25.77 4,530 74.23 <0.001
Ever drink 550 31.41 1,201 68.59
Current drink 529 33.87 1,033 66.13
Frequency of watching television
Not at all 1,623 27.94 4,186 72.07 0.901
Less than once a week 423 28.33 1,069 71.60
At least once a week 606 28.64 1,509 71.31
Ever report of contraceptive use
No method 1,132 21.97 4,020 78.03 <0.001
Traditional method 821 34.24 1,577 65.76
Non-hormonal method 259 36.79 446 63.35
Hormonal method 441 37.92 722 62.08
Place of residence
Urban 1,203 29.90 2,821 70.10 0.028
Rural 1,449 26.87 3,944 73.13
Region
Plain 1,408 29.91 3,299 70.07 0.006
Tonle Sap 768 26.86 2,092 73.17
Coastal 171 28.74 425 71.43
  Plateau/Mountain 306 24.38 949 75.62  
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Notes: Survey weights are applied to obtain weighted percentages. Plains: Phnom Penh, Kampong Cham, Tbong Khmum, Kandal, Prey Veng, Svay Rieng, and Takeo; Tonle Sap: Banteay Meanchey, Kampong Chhnang, Kampong Thom, Pursat, Siem Reap, Battambang, Pailin, and Otdar Meanchey; Coastal/sea: Kampot, Kep, Preah Sihanouk, and Koh Kong; Mountains: Kampong Speu, Kratie, Preah Vihear, Stung Treng, Mondul Kiri, and Ratanak Kiri.

Factors associated with overweight and obesity in adjusted logistic regression

As shown in Table 3, several factors were independently associated with increased odds of being overweight and obese among women. These factors included age group 20–29 years [AOR = 1.85; 95% CI: 1.22–2.80], 30–39 years [AOR = 3.34; 95% CI: 2.21–5.04], and 40–49 years [AOR = 5.57; 95% CI: 3.76–8.25] married [AOR = 2.49; 95% CI: 1.71–3.62] and widowed/divorced/separated [AOR = 1.14; 95% CI: 1.14–2.63], middle wealth quintile [AOR = 1.21; 95% CI: 1.02–1.44], and rich wealth quintile [AOR = 1.44; 95% CI: 1.19–1.73], having at least three children or more [AOR = 1.40; 95% CI: 1.00–1.95], ever drink alcohol [AOR = 1.24; 95% CI: 1.04–1.47], and current drink alcohol [AOR = 1.21; 95% CI: 1.01–1.45]. On the contrary, the following factors were independently associated with decreased odds of being overweight and obese: women with at least secondary education [AOR = 0.73; 95% CI: 0.58–0.91], working in manual labor jobs [AOR = 0.76; 95% CI: (0.64–0.90] (see Fig 2).

Table 3. Risk factors associated with overweight and obesity in unadjusted and adjusted logistic regression analysis.

Characteristics Unadjusted (n = 9,417) Adjusted (n = 9,225)
OR 95%CI AOR 95%CI
Women’s age group in years
15–19 Ref. Ref.
20–29 3.71*** (2.61–5.27) 1.85 *** (1.22–2.80)
30–39 9.25*** (6.70–12.77) 3.34 *** (2.21–5.04)
40–49 15.84*** (11.68–21.47) 5.57 *** (3.76–8.25)
Marital status
Not married Ref. Ref.
Married or living together 6.96*** (5.67–8.54) 2.49 *** (1.71–3.62)
Widowed/divorced/separated 5.34*** (3.81–7.50) 1.73 ** (1.14–2.63)
Education
No education  Ref. Ref.
Primary  0.86 (0.72–1.03) 0.97 (0.80–1.17)
Secondary and higher  0.43*** (0.35–0.53) 0.73 *** (0.58–0.91)
Current work status
Not working Ref. Ref.
Agricultural 1.37*** (1.14–1.64) 0.85 (0.69–1.03)
Professional 1.63*** (1.40–1.89) 1.13 (0.93–1.35)
Manual labor and unskilled 1.00 (0.85–1.19) 0.76 *** (0.64–0.90)
Number of children born
No birth Ref. Ref.
1–2 child 4.41*** (3.61–5.38) 1.23 (0.89–1.68)
Three and above 7.03*** (5.79–8.55) 1.40 ** (1.00–1.95)
Household wealth index
Poor Ref. Ref.
Middle  1.18** (1.02–1.37) 1.21 ** (1.02–1.44)
Rich 1.35*** (1.18–1.56) 1.44 *** (1.19–1.73)
Smoking
Non-smoker Ref. - -
Smoker 0.81 (0.52–1.24) - -
Current drinking alcohol
Never drink Ref. Ref.
Ever drink 1.32*** (1.13–1.54) 1.24 ** (1.04–1.47)
Current drink 1.47*** (1.23–1.76) 1.21 ** (1.01–1.45)
Watching television
Not at all Ref. - -
Less than once a week 1.02 (0.85–1.23) - -
At least once a week 1.04 (0.89–1.21) - -
Ever report of contraceptive use
No method Ref. Ref.
Traditional method 1.85*** (1.61–2.12) 1.02 (0.86–1.21)
Non-hormonal method 2.06*** (1.64–2.60) 0.84 (0.65–1.10)
Hormonal method 2.17*** (1.75–2.69) 1.01 (0.81–1.26)
Place of residence
Rural Ref. Ref.
Urban 1.16** (1.02–1.33) 1.11 (0.94–1.31)
Region
Plain Ref. Ref.
Tonle Sap 1.33*** (1.11–1.58) 1.17 (0.95–1.43)
Coastal 1.14 (0.95–1.36) 1.11 (0.91–1.35)
  Plateau/Mountain 1.25** (1.00–1.55) 1.10 (0.86–1.41)
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Notes: Survey weights are applied to obtain weighted percentages. *** p<0.01

** p<0.05

* p<0.10.

Fig 2. Adjusted analyses of the odds of women of reproductive age being overweight and obese in Cambodia (n = 9,225).

Fig 2

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Discussion

The overall prevalence of overweight and obesity among WRA in Cambodia was 22.56% (95% CI: 21.5–23.7) and 5.61% (95% CI: 5.0–6.3), which was higher than the percentage of WRA who were the overweight and obesity in 2000 (6% and 2%), as well as in 2014 (18% and 2.8%) [3]. This continuous increase is becoming a public health problem in the country. Our findings were consistent with the findings in Global Nutrition Report 2019 where 26.1% and 6.3% of women were overweight and obese respectively [6]. At the same time, overweight and obesity is highest proportion among WRA residing in active economic provinces such as Kampong Cham, Kandal, Svay Rieng, Preah Sihanouk, Phnom Penh (see Fig 1). The variation and increase in overweight and obesity in Cambodia could be due to lifestyle changes and urbanization [11]. For example, the consumption of fast foods high in sugar, fat and salt has become widespread [11]. High prevalence of women consumed sweet beverages, and consumed unhealthy foods the previous day and drinking alcohol in past 30 days were also fund in CDHS 2021–22 [8]. Furthermore, physical activity has decreased due to improved transportation [8, 11].

Older aged women were more likely to be overweight or obese as compared to younger women aged 15–19 years. This is consistent with other studies that showed obesity was more prevalent in older WRA [3, 26]. The risk of women becoming overweight or obese rises with age, possibly due to unhealthy food consumption and a lack of physical activity [27]. Married women were more likely to be overweight or obese as compared to single women. Similar to previous study on the prevalence of overweight and obesity among WRA and its associated factors utilized CDHS data since 2014 [3], and in line with pooled analysis of DHS data among WRA in Bangladesh, Nepal, and India [28]. The explanation for that could be that married women busy working and take care their children and family may they do not pay more attention to nutritional and physical activity [3]. Women with better socioeconomic status and who live in urban areas had higher odds of being overweight and obese, which is consistent with prior research [29, 30]. Women with higher socioeconomic status tend to use more improved technologies for a more comfortable lifestyle [19, 31]. Women have at least three and more children at risk of being overweight and obese, similar to other studies [3, 32]. During pregnancy, factors such as stress, depression, and anxiety may play a role in hypothalamic-pituitary-adrenal hyperactivity [33, 34]. Women with several children may also have gained weight due to their reduced physical activity and have less time to focus on health behaviors, including weight management. In addition, women ever and currently consuming alcohol were significantly associated with higher risks of being overweight and obese. The association between alcohol consumption status and overweight and obesity has been studied thoroughly in various populations, such as Urban Cambodia and Hawassa City, southern Ethiopia [20, 21]. Commonly, alcohol consumption is considered to increase appetite, resulting in excessive energy intake and leading to overweight and obesity [35]. In contrast, women with higher education are less likely to be overweight or obese than women with no school due to increased knowledge and awareness; for example, studies in Cambodia, Nigeria, and South Korea reported that educated women had a lower risk of being overweight or obese and that this may be linked to education influencing healthy behavior [3, 36–39]. Education is a critical predictor of women’s healthy behaviors and health outcomes, including diet and physical activity [40]. Although overweight and obesity were not significantly associated with geographical regions of residence and place of residence in multiple logistic regression, we found that the rates of overweight and obesity among women in the Plain and Coastal regions were higher than those living in other regions, at 29.91% and 28.74%, respectively. Also, the prevalence of overweight and obesity among women in urban regions was greater than that of women in rural areas (29.90% vs. 26.87). Previous research on overweight and obesity among women of reproductive age in Cambodia found that women residing in urban had a significant association with overweight and obesity [3], suggesting a need for further regionally representative studies.

Our study had few limitations. First, because CDHS 2021–2022 collected cross-sectional data, our analysis could not explore changes over time. Second, data on several critical variables, such as women’s food-consumption behaviors, were not collected by CDHS, and CDHS did not objectively measure physical activity. Therefore, our ability to examine the association of these variables with overweight and obesity was restricted. Third, numerous psychological factors (e.g., depressive and anxiety disorders) and physiological factors may also be associated with overweight and obesity. Still, these factors were not included in this study because they were unavailable in the data set. Finally, because the data were available only for women aged 15 to 49, our results could not be generalized to girls younger than 15 and women older than 49. Despite these limitations, our results contributed to the literature on the prevalence and association between socio-demographic and behavioral variables and the status of overweight and obesity among women of reproductive age in Cambodia. However, the major strength of this study was the use of nationally representative data with a high response rate of 97% to examine the prevalence and predictors of overweight and obesity in this country. Data were collected using validated survey methods, including calibrated measurement tools and highly trained data collectors, contributing to improved data quality [41]. Finally, incorporating the complex survey design and sampling weights into the analysis bolstered the rigor of the findings and enables generalizing our findings to the population of non-pregnant women in Cambodia.

In conclusion, the present study indicated that the prevalence of overweight and obesity among WRA in Cambodia was very high during 2021–22. Furthermore, the main factors that significantly increased the odds of being overweight and obese were older age, married status, living in a rich household wealth index, and drinking alcohol, while higher education levels and manual labor or unskilled employment reduced the odds of being overweight and obesity. Therefore, there is an urgent need to take interventions that target women from higher socio-demographic status to reduce the risk of life-threatening caused by being overweight and obese through raising awareness of the importance of consuming healthy food, and the benefits of regular physical activity, especially among older women monitor their weight, blood pressure and blood sugar with healthcare profession.

Supporting information

S1 Table. Results of checking multicollinearity using Variance Inflation Factor (VIF).

(DOCX)

Click here for additional data file. (14.2KB, docx)
S2 Table. Prevalence of overweight and obesity among women reproductive age, CDHS 2021–2022 (n = 9,417).

(DOCX)

Click here for additional data file. (17.1KB, docx)

Acknowledgments

The authors would like to thank DHS-ICF, who approved the data used for this paper.

Data Availability

Our study used the 2021-2022 Cambodia Demographic and Health Survey (CDHS) datasets. The DHS data are publicly available from the website at (URL:https://www.dhsprogram.com/data/available-datasets.cfm). The Shapefiles for administrative boundaries in Cambodia are publicly accessible through the DHS website at (URL:https://spatialdata.dhsprogram.com/boundaries/#view=table&countryId=KH).

Funding Statement

The authors received no specific funding for this work.

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0002537.r001

Decision Letter 0

Abraham D Flaxman

4 Oct 2023

PGPH-D-23-01290

Factors Associated with Overweight and Obesity among Women of Reproductive Age in Cambodia: Analysis of Cambodia Demographic and Health Survey

PLOS Global Public Health

Dear Dr. Um,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

The review's comment about a Directed Acyclic Graph (DAG) seems like something that could be a valuable addition to your exposition, and I would like to see your revision include a DAG that represents the causal relationships that you hypothesize are present between the factors you have included in your analysis.  I believe that this DAG will also provide a crisp framework for you to address the reviewer's question about what specifically your paper adds to the existing knowledge.

==============================

Please submit your revised manuscript by Nov 18 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Abraham D. Flaxman, Ph.D.

Academic Editor

PLOS Global Public Health

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Reviewer #1: Partly

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

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Reviewer #1: Yes

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Reviewer #1: This paper aimed to determine the prevalence and factors associated with overweight and obesity among women of reproductive age (WRA) in Cambodia. The authors used the Cambodia Demographic and Health Survey (CHDS) as the data source and, therefore were able to provide nationally representative data. Considering the rise of overweight/obesity among WRA in Cambodia (i.e. 18% in 2014 to 39% in 2021-2022), this study raised an important emerging issue in the country.

Main comments:

- The first main concern is on Table 3. This analysis approach is referred as “Table 2 Fallacy”, in which all estimates were interpreted in the same way as total-effect estimates. Meanwhile, the interpretation of a confounder effect estimate may be different than for the exposure effect estimate (e.g. total effect for main exposure vs. direct effect for covariates). This is the key article explaining about this issue: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626058/ , and here is a concrete example that quantitatively illustrate the potential of misinterpretation: https://pubmed.ncbi.nlm.nih.gov/29782045/. A Directed Acyclic Graph (DAG) that presents the conceptual framework of the study would help to carefully clarify this problem e.g. Have all potential confounders been considered? Are any of the factors on the causal pathway between one factor and the outcome? The current approach used in this paper should be acknowledged as substantial limitations to draw causal conclusions.

- Considering that the factors included in the analysis have been known associated with overweight/obesity, what does this paper add to the existing knowledge?

Introduction:

- Authors could add explanations on trends that occurred in Cambodia, e.g. lifestyle changes, that may lead to the increase of overweight/obesity prevalence among WRA. Hence, this will highlight the importance of the study.

- p.3 line 62: Why is the prevalence of overweight/obesity among WRA based on CDHS mentioned in the introduction (i.e. 39%) different from the study result (i.e. 22.56% overweight + 5.61% obesity = 28.17)?

- p.3 line 65-74: Are these predictors of overweight/obesity among WRA based on global data/other countries’ data?

Material and Methods:

Clear explanation on methods part. Below are minor feedback for this section:

- p.4 line 8-9: This “From September 15, 2021, to February 15, 2022” seems an incomplete sentence.

- p.5 line 36: “Normal weight“ should be used instead of “average weight”.

Results:

- The number of subjects included (n) can be restated at the beginning of the section.

- p.7 line 98: Missing percentage symbol on “18.60”

- p.7 line 99: Should be 22.56% instead of 22,56%

- Table 1: n of obese women had decimal i.e. 528.2 – can the author confirm this? Please check the consistency of using “()” instead of “[]” on the 95%CI in the BMI status rows.

- p.9 line 27-43 and Table 2: This paragraph was written as if the authors did post-hoc analyses, which were not the case. For instance, it could not be concluded that women who used non-hormonal contraceptive methods had a significantly higher proportion of overweight/obesity than women using other methods (line 38); This is a type of conclusion that can be drawn from a posthoc analysis or if any regrouping were done. I wonder if that is the case since the p-value for contraceptive use as the predictor on page 10 line 238 (i.e. <0.019) is different from the p-value provided in Table 2 (i.e. 0.001).

- Please add explanation for the use of bold text in certain numbers within Table 2.

Discussion:

- It needs more explanation on the findings in overweight/obesity prevalence e.g. how is this finding compared to previous studies/years and/or other countries? Why there were substantial differences in the prevalence across provinces (e.g. 34.1% in Kampong Cham vs. 9.4% in Ratanak Kiri)?

- Based on the findings of the current analysis, it needs an explanation on how marital status emerged as significant predictor of overweight/obesity.

Conclusion:

Please clarify regarding the statement “design intervention programs that target these sociodemographic factors”. For instance, given that higher education levels and income are associated with overweight/obesity in this study – should women reduce their socioeconomic status? Similarly, since older age is linked to higher odds, should interventions aiming to reducing women’s age?

**********

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Reviewer #1: No

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0002537.r003

Decision Letter 1

Abraham D Flaxman

30 Nov 2023

PGPH-D-23-01290R1

Factors Associated with Overweight and Obesity among Women of Reproductive Age in Cambodia: Analysis of Cambodia Demographic and Health Survey

PLOS Global Public Health

Dear Dr. Um,

Thank you for submitting your manuscript to PLOS Global Public Health. After careful consideration, we feel that it has merit but does not fully meet PLOS Global Public Health’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Reviewer 2 corresponded with me to clarify that the manuscript isn’t “wrong” just there are aspects that are debatable or not comprehensive enough. Can you revise in response to their comments, and focus on more cautious interpretation of odds ratios, to make sure you are not claiming to prove a causal link with observational data?

==============================

Please submit your revised manuscript by Dec 30 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at globalpubhealth@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pgph/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Abraham D. Flaxman, Ph.D.

Academic Editor

PLOS Global Public Health

Journal Requirements:

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

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2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #2: Partly

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: No

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4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: This manuscript investigated the factors associated with overweight and obesity in Cambodia using the latest Demographic and Health Survey (DHS) data. It focused on women of reproductive age and examined sociodemographic variables and selected behavioral risk factors such as use of contraceptives, smoking, and alcohol use. While the study provided some insight into the obesity epidemic in Cambodia, several aspects could be improved:

1. Factors associated with overweight and obesity: The authors acknowledged the omission of diet and physical activity from the study's considered factors, which are crucial direct influences on overweight and obesity outcomes. Although understanding the contribution sociodemographic factors to overweight and obesity is useful, it only offers a distal perspective, leaving a gap in understanding the most immediate factors.

2. Goodness of fit: The manuscript does not clarify the extent to which the selected variables in the multiple logistic regression account for variability in the data. Questions remain regarding the fit of the regression model and the proportion of unexplained variance.

3. Interpretation of AOR: Setting aside concerns of multicollinearity and model fit, the interpretation of results in Table 3 is convoluted. The odds ratios of several factors shifted from significant to non-significant after adjustment, with urban versus rural residency as an example. This change was likely due to the inclusion of other relevant factors such as occupation and wealth. However, the change of significance did not imply occupation being more important than place of residence. It was unclear, what conclusion should be drawn from the results in Table 3 comparing between OR and AOR.

4. Comparisons with the 2014 study: The study could benefit from a more detailed comparison with the DHS 2014 study. The current manuscript essentially replicated the previous study with new DHS data and the conclusion were similar. It would be informative to delineate the differences, changes over the decade, and any new insights provided by the latest research.

Other comments:

- Page 4, line 120: The term "height and length" should be revised to "height" when referring to adults.

- The general flow and coherence between sentences and paragraphs could be enhanced with editorial support.

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For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0002537.r005

Decision Letter 2

Abraham D Flaxman

9 Jan 2024

Factors Associated with Overweight and Obesity among Women of Reproductive Age in Cambodia: Analysis of Cambodia Demographic and Health Survey

PGPH-D-23-01290R2

Dear Mr. Um,

We are pleased to inform you that your manuscript 'Factors Associated with Overweight and Obesity among Women of Reproductive Age in Cambodia: Analysis of Cambodia Demographic and Health Survey' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact globalpubhealth@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Abraham D. Flaxman, Ph.D.

Academic Editor

PLOS Global Public Health

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Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

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2. Does this manuscript meet PLOS Global Public Health’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS Global Public Health does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Results of checking multicollinearity using Variance Inflation Factor (VIF).

    (DOCX)

    Click here for additional data file. (14.2KB, docx)
    S2 Table. Prevalence of overweight and obesity among women reproductive age, CDHS 2021–2022 (n = 9,417).

    (DOCX)

    Click here for additional data file. (17.1KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (26.5KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (20.3KB, docx)

    Data Availability Statement

    Our study used the 2021-2022 Cambodia Demographic and Health Survey (CDHS) datasets. The DHS data are publicly available from the website at (URL:https://www.dhsprogram.com/data/available-datasets.cfm). The Shapefiles for administrative boundaries in Cambodia are publicly accessible through the DHS website at (URL:https://spatialdata.dhsprogram.com/boundaries/#view=table&countryId=KH).

    Articles from PLOS Global Public Health are provided here courtesy of PLOS

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