Association between socioeconomic factors and soft drink consumption among adults in Cambodia: a cross-sectional study

Wonga Laohasiriwong; Sim Samphors; Pall Chamroen; Vong Pisey; Rebecca S. Dewey

doi:10.12688/f1000research.24890.2

Home Browse Association between socioeconomic factors and soft drink consumption...

ALL Metrics

Views

Downloads

Get PDF

Get XML

Export

▬

✚

Research Article

Revised

Association between socioeconomic factors and soft drink consumption among adults in Cambodia: a cross-sectional study

[version 2; peer review: 1 approved with reservations]

Wonga Laohasiriwong¹, Sim Samphors ², Pall Chamroen³, Vong Pisey⁴, Rebecca S. Dewey⁵

Wonga Laohasiriwong¹, Sim Samphors ², [...] Pall Chamroen³, Vong Pisey⁴, Rebecca S. Dewey⁵

PUBLISHED 28 Sep 2020

Author details Author details

¹ Faculty of Public Health, Khon Kaen University, Khon Kaen, 40002, Thailand
² Graduate School, Chea Sim University of Kamchaymear, Prey Veng, Cambodia
³ KHANA Center for Population Health Research, Prey Veng, Cambodia
⁴ Office of Rural Health Care, Ministry of Rural Development, Ministry of Rural Development, Cambodia
⁵ University of Nottingham, Nottingham, UK

Wonga Laohasiriwong
Roles: Conceptualization, Methodology, Supervision, Validation

Sim Samphors
Roles: Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Software, Supervision, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Pall Chamroen
Roles: Conceptualization, Project Administration, Resources, Writing – Review & Editing

Vong Pisey
Roles: Conceptualization, Methodology, Software, Validation, Visualization, Writing – Original Draft Preparation

Rebecca S. Dewey
Roles: Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Global Public Health gateway.

Abstract

Background: Soft drinks are an attractive and popular drink, consumed by many people to fulfill their energy. However, soft drink consumption is an important risk factor for non-communicable diseases. This study aimed to investigate the association between socioeconomic factors and soft drink consumption among adults in Cambodia.
Methods: A cross-sectional analytical study with multi-stage random sampling was used to select 749 respondents from 12 communes across 5 districts in Phnom Penh, the capital city of Cambodia. A structured questionnaire was used to assess socioeconomic factors and soft drink consumption. Data were analyzed using bivariate and multivariable logistic regression. Crude odds ratios and adjusted odds ratios (AORs) with 95% confident intervals (CI) were calculated to show the strength of associations.
Results: The overall prevalence of soft drink consumption was 44.73% (95%CI: 41.16-48.30%) across the sample population. The final model of multiple logistic regression showed only four factors to be significantly associated with soft drink consumption: gender, age, family size and income. Respondents most likely to consume soft drinks were men (AOR: 1.49, 95%CI: 1.10-2.00; p=0.009), those aged 31-59 years (AOR: 1.93, 95%CI: 1.98-4.62; p<0.001), those in a household of less than 5 individuals (AOR: 1.38, 95%CI: 1.44-3.19; p=0.036), and those earning <300$/month (AOR: 1.59, 95%CI: 1.10-2.31; p=0.003).
Conclusion: The prevalence of soft drink consumption in Cambodia is a major concern for public health. The predictive factors significantly associated with soft drink consumption identified by this study were gender, age, household size and income. Therefore, all stakeholders should contribute to social marketing and intervention focusing on reducing the consumption of soft drinks through advertising on social media, television and other popular media platforms. Furthermore, additional taxation of soft drinks should be considered.

Keywords

Socio-economic, adults, multiple logistic regression, Cambodia

Corresponding author: Sim Samphors

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2020 Laohasiriwong W 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 work is properly cited.

How to cite: Laohasiriwong W, Samphors S, Chamroen P et al. Association between socioeconomic factors and soft drink consumption among adults in Cambodia: a cross-sectional study [version 2; peer review: 1 approved with reservations]. F1000Research 2020, 9:708 (https://doi.org/10.12688/f1000research.24890.2) First published: 15 Jul 2020, 9:708 (https://doi.org/10.12688/f1000research.24890.1) Latest published: 09 Aug 2021, 9:708 (https://doi.org/10.12688/f1000research.24890.3)

Revised Amendments from Version 1

We have updated the authorship of article by adding Pall Chamroen and Wongsa Laohasiriwong.

See the authors' detailed response to the review by Prince Atorkey

Introduction

Nutritional status is a principle determinant of health. Assessment of nutritional status, dietary intake, and related factors are of worldwide importance to public health. Although recent studies reported that nutritional status has improved remarkably over the last few decades, the rates of people being classed as underweight or overweight remain high. In general, being overweight/obese or underweight severely affect an individual’s health and their quality of life, increase their risk of developing infectious diseases, reduce their ability to work, prolong hospitalization and increase the risk of illness and death. Thus, achieving and maintaining an ideal body weight is highly advisable^1,2.

There are many factors influencing becoming overweight and obese. Lifestyle, cultural activities, socioeconomic factors, physical inactivity and diet are the main factors that have been found to have an association with being overweight and obese^3–6. Many studies have reported that one of the main factors influencing becoming overweight and obese is inappropriate diet, especially soft drink consumption^7–10.

Soft drinks provide little nutritional value and are energy-dense¹¹. Dietary patterns have changed rapidly throughout the world, especially in Western countries where consumption of soft drinks is popular¹². However, this trend has been extended across Asian countries, including Cambodia, where soft drink consumption has replaced nutritional Asian foods such as fish, vegetables and other less energy-dense foods.

A number of developing and developed countries in the world are facing what is described by the World Health Organization (WHO) as the double burden of malnutrition, the simultaneous impacts of undernutrition and overweightness/obesity¹³. Research has shown the prevalence of individuals being overweight to be significantly higher in urban compared to rural areas¹⁴. However, the true relationships between socioeconomic factors and soft drink consumption among adults in urban Cambodia is hitherto unknown.

As such, the present study aimed to determine the association between socioeconomic factors and soft drink consumption of adults in Phnom Penh, the urban metropolis of Cambodia, providing vital information for public health professionals and policy makers in order to prepare educational programs and interventional policies.

Methods

Study setting and design

A structured questionnaire was administered from March, 2018 to July, 2018 at participant homes in participants’ free time using a cross-sectional multi-stage random sampling method in order to select 749 samples among 12 communes out of 5 districts in the Phnom Penh municipality of Cambodia.

The study design was reviewed by the Khon Kaen University ethics committee and was approved for human research (Reference No. HE582071). Data collection was conducted by administering the questionnaire in a face-to-face interview. All participants gave written informed consent to participate in the study. If the participant was unable to read the consent form, the researcher read it aloud for them.

Study participants

Multi-stage random sampling was used to select the samples in this study. Phnom Penh capital city was selected and 5 districts were randomly selected from the total of 12 districts of Phnom Penh capital city. Then 2 or 3 communes were randomly selected from each selected district, for a total of 12 communes to be selected. Each household in each commune was listed and assigned a number and a systematic random sampling procedure was used to select 748 households from the total 44,436 households. Finally, one member aged 18-59 of each household was randomly selected if the household had more than one member in this age category.

The inclusion criteria for the study were that participants over 18 years of age, and were able to understand the questionnaire. Exclusion criteria were any serious health problems (causing them to be bedbound), diarrhea at the time of data collection (defecating more than 3 times per day), pregnancy, mental illness, deformity and lower limb amputation.

The sample size for this study was calculated using an established formula¹⁵ and the estimated sample size was 749.

The outcome measure used in this study is soft drink consumption, for which a threshold of ≥3 times per week was chosen. This threshold was used as it has been previously associated with being overweight/obese, and having metabolic syndrome^16–18.

Questionnaire

A structured questionnaire was developed based on the research questions and relevant literature. The questionnaire consisted of two parts: part 1, demographic and socioeconomic characteristics, including gender, age, marital status, educational attainment, occupation, number of family members and personal monthly income; part 2, lifestyle and behavior characteristics, including tobacco use, alcohol consumption, food habits, soft drink consumption, physical activity and sedentary behavior.

As the questionnaires were developed for data collection, a pre-test of the questionnaire was conducted in 30 participants from different areas from the target group. Reliability was calculated using Cronbach’s alpha coefficient, and was 0.857. Then the questionnaire was developed and tested for content validity by five experts. Finally, a forum of researchers edited and rearranged the questionnaire based on the results of the field test, with the aim to ensure the validity and reliability of the tool.

Dependent variable. Participants consuming soft drinks more than three times per week was the dependent variable used in this study. Participants were asked “How many times per week have you drunk a soft drink in the last month?” Participant answers were classified into two groups: those who drank soft drinks less than 3 times per week (“no” = 0) and 3 times per week of more (“yes” = 1).

Predictor variables. Age, household income and expenditure, and the number of individuals in the household were coded as continuous variables. Categorical variables comprised gender (male or female), marital status (single, married or divorced), level of education (no formal education, primary, secondary, high school, associated degree, Bachelor’ degree, Master’s degree or higher), occupation (farmer, unemployed, NGO employee, self-employed, student, government officer, home maker, unskilled worker, or other) and the people they were cohabiting with (spouse, parents, relatives, none, friend, or other).

Statistical analysis

Data were imported to Stata version 13 (College Station, Texas, USA) for analysis. Continuous and categorical data were inspected using descriptive statistics to determine the frequencies and percentages (categorical variables) and means, medians and standard deviations (continuous variables) of each socio-economic and demographic characteristic collected. Bivariate logistic regression was used to estimate the association between each socioeconomic factor and the outcome measure of soft drink consumption. Crude odds ratios (CORs) were computed using 95% confidence intervals (CIs) and variables with significance of p<0.25 were entered into the final model. In this final model, multivariate logistic regression was used to estimate the association between socioeconomic factors and soft drink consumption. Adjusted odds ratios (AORs) were then computed using the 95% CI. Significance was considered at a threshold of p<0.05.

Results

Socioeconomic characteristics of the participants

A total of 749 participants from 5 districts and 12 communes were recruited into the study. The socio-demographic characteristics of respondents are summarized in Table 1. In total, 50.2% of participants were women and 49.80% were men, and the mean age of participants (± standard deviation) was 32.26±11 years. The marital status of participants was 53.94% married, 43.52% single and 2.54% divorced. The most frequent level of participants’ highest educational attainment was high school (31.91%), followed by Bachelor’s degree (26.44%) and primary school level (15.22%). The most frequent occupations were private company workers (28.97%), self-employed (21.36%) and students (20.16%), with only 0.67% of the participants being farmers and 0.93% unemployed. More than half of the participants (57.41%) had a household size of less than 5 members, and participants most frequently reported living with their spouse (47.93%), parents (25.37%) and relatives (12.95%). Monthly income ranged from US$40 to $5,100 with a mean (±SD) of US$495±686.7. Monthly expenditure ranged from US$20 to $3,750 USD with mean of US$288.5±394.1 (see Table 1).

Table 1. Baseline characteristics of respondents (n=749).

Characteristics	N (%)
Gender
Male	373 (49.80)
Female	376 (50.20)
Age (years)
18–20	106 (14.15)
21–30	253 (33.78)
31–40	229 (30.57)
41–50	98 (13.08)
>50	63 (8.41)
Mean (SD)	32.26±11
Median (Min: Max)	30 (18-59)
Marital status
Single	326 (43.52)
Married	404 (53.94)
Widowed	19 (2.54)
Highest level of education
Master’s degree or higher	15 (2.00)
No formal education	69 (9.21)
Bachelor’s degree	198 (26.44)
Secondary school	95 (12.68)
Associated degree	19 (2.54)
Primary school	114 (15.22)
High school	239 (31.91)
Occupation
Unemployed	7 (0.93)
Housewife	48 (6.41)
Student	151 (20.16)
Farmer	5 (0.67)
Self-employed	160 (21.36)
Unskilled worker	25 (3.34)
Private company worker	217 (28.97)
NGO employee	11 (1.47)
Government officer	69 (9.21)
Others	56 (7.48)
Household size (number of persons)
<5	430 (57.41)
≥5	319 (42.59)
Household constituents
Parents	190 (25.37)
Alone	50 (6.68)
Others	20 (2.97)
Spouse	359 (47.93)
Relatives	97 (12.95)
Friend	33 (4.41)
Income (USD/Month)
>300	316 (42.19)
≥300	433 (57.81)
Mean (±SD)	495 (±686.7)
Median (Min: Max)	300 (40-5,100)
Expenditure (USD/Month)
>500	526 (70.27)
≥500	223 (29.77)
Mean (±SD)	288.5 (±394.1)
Median (Min: Max)	200 (20-3,750)

Factors associated with soft drink consumption with simple logistic regression

The overall prevalence of soft drink consumption was 44.73% (95%CI: 41.16-48.30%). Educational attainment, gender, age, occupation, household composition, household size, and income were found to have associations with soft drink consumption (p<0.25) in the bivariate analysis (Table 2).

Table 2. Odds ratio (ORs) of socioeconomic factors associated with soft drink consumption (SDC) and their 95% confidence intervals (CIs) (n=749).

Characteristics	N	%SDC	OR	95%CI	p-value
Overall	749	44.73	N/A	41.16-48.30	N/A
Gender					0.037
Female	376	40.96	1
Male	373	48.53	1.36	1.02 - 2.81
Age (years)					<0.001
31–59	390	36.67	1
18–30	359	53.48	1.98	1.48-2.66
Marital status
Married	404	39.60	1		0.002
Unmarried	345	50.72	1.60	1.17- 2.09
Educational attainment					0.042
≤High school	278	39.93	1
>High school	471	47.56	1.36	1.01-1.84
Occupation					0.051
Employed	543	42.54	1
Unemployed	206	50.49	1.38	0.99- 1.90
Household size (persons)					0.112
≥5	319	41.38	1
<5	430	47.21	1.27	0.94- 1.70
Household constituents					0.532
With Family	646	44.27	1
Without Family	103	47.57	1.14	0.75-1.73
Income (US Dollar/Month)					0.001
≥300	433	39.26	1
<300	316	52.22	1.69	1.26- 2.27
Expenditure (US Dollar/Month)					0.212
≥500	223	41.26	1
<500	526	46.20	1.22	0.89-1.68

Factors associated with soft drink consumption with multiple logistic regressions

The final model found only four factors associated with soft drink consumption: gender, age, household size and income. Men (AOR: 1.49, 95%CI: 1.10-2.00; p = 0.009), those aged 31-59 years (AOR: 1.93, 95%CI: 1.98-4.62; p <0.001), those in smaller households (AOR: 1.38, 95%CI: 1.44-3.19; p = 0.036), and those earning <US$300/month (AOR: 1.59, 95%CI: 1.10-2.31; p = 0.003) were more likely to consume soft drinks at least three times a week (Table 3).

Table 3. Adjusted odds ratio (ORs) of socioeconomic factors associated with soft drink consumption (SDC) and their 95% confidence intervals (CIs) (n=749).

Characteristics	N	%SDC	Crude OR	Adjusted OR	95%CI	p-value
Overall	749	44.73	N/A	N/A	41.16-48.30	N/A
Gender						0.009
Female	376	31.65	1	1
Male	373	45.84	1.36	1.49	1.10-2.00
Age (years)						<0.001
≤30	359	21.45	1	1
≥31	390	54.62	1.98	1.93	1.98-4.62
Household size						0.036
≥5	319	41.38	1	1
<5	430	47.21	1.27	1.38	1.44-3.19
Income (US Dollar/Month)						0.003
≥300	342	39.26	1	1
<300	407	52.22	1.69	1.59	1.10-2.31

Discussion

This study found that the prevalence of soft drink consumption among Cambodian adults was 44.73% (95%CI: 41.16–48.30). Almost one-third of adults aged 18–59 consumed soft drinks more than 3 times per week in Cambodia. The trend of soft drink consumption has rapidly increasing over a period of the last few years¹⁹, during which time the Cambodian economy has increased twofold in economic growth rates. Globally, the consumption of soft drinks is higher in upper-middle income countries (0.8 servings per person per day) compared to the lower-middle income countries (0.59 servings per day)²⁰. The findings of the present study are consistent with findings from Malaysia showing that 53.3% of individuals consume soft drinks three times per week or more²¹, with similar findings also in Saudi Arabia (40%) and Nigeria (42.8%). Daily consumption has been reported in developed countries such as the USA (40%)²² and the UK (20.4%)²³ and similarly in South Africa (48.3%)²⁴. This may be related to the culture of western and European countries preferring fast food and artificially sweetened soft drinks. Furthermore, there may be a tendency towards busier lifestyles with less emphasis on making time to cook. In the present study, the factors associated with soft drink consumption were found to be gender, age, household size and income.

Gender was found to be significantly associated with soft drink consumption. Men were more likely (AOR: 1.49; 95%CI:1.10-2.00) to consume soft drinks compared to their female counterparts. This finding is consistent with a study from the USA, which revealed that men were more likely to consume soft drinks than women²². A study in Australia also found the men are 2.11 times more likely to consume soft drinks compared to women¹¹. In the context of Cambodia, it might be that men go out to work more often, requiring more energy and undertake activities where soft drinks are often consumed in order to counteract fatigue both during and after work.

Many studies have found age to be significantly associated with soft drink consumption, and the present study’s results support this. Our finding was that 31–59-year-olds are more likely to consume soft drinks compared to 18–30-year-olds (AOR:1.93; 95%CI: 1.98-4.62). However, there are also published studies that contradict this finding^11,21. The age range in the present study was 18–59-year-olds; therefore, the older age bracket (31 to 59) are likely to be in paid employment, and not yet in retirement. These individuals may be more likely to consume soft drinks to combat fatigue while working, and this may be more prevalent amongst older individuals within the subgroup.

Finally, income was found to be significantly associated with soft drink consumption. Those who earned less than US$300 per month were more likely to consume soft drinks (AOR:1.59; 95%CI: 1.10-2.31) compared to those who earned more than US$300 per month. This finding is consistent with research from Singapore showing that high and medium earners consumed less soft drinks when compared to low earners¹¹. Conversely, a study from Australia reported that households with higher annual incomes were more likely to consume soft drinks compared to households with lower annual incomes²⁴.

Conclusion

The prevalence of soft drink consumption in Cambodia has become a recent concern for public health. Predictive factors found in this study that are significantly associated with higher soft drink consumption are being a man, aged 31–59 years, living in a household of less than 5 individuals, and having a monthly income of less than US$300.

Based on our research findings, we recommend taking measures to reduce the frequency of soft drink consumption. All stakeholders within each ministry in Cambodia should promote and raise awareness of the impacts of soft drink consumption within the population. Specifically, the Ministry of Health should develop and launch a social marketing and intervention program focusing on reducing the consumption of soft drinks through advertising on social media, television and other means. Furthermore, the taxation of soft drinks should be considered.

Data availability

Underlying data

Figshare: Underlying Data 1, https://doi.org/10.6084/m9.figshare.12612998.v1²⁵

This project contains the following underlying data:

- Raw data from a survey the consumption of fast food and soft drinks in Phnom Penh municipality of Cambodia in 2019.
- Code book for interpreting the data

Extended data

Figshare: Extended data, https://doi.org/10.6084/m9.figshare.12612992.v1²⁶

This project contains the following extended data:

- Questionnaire in Khmer
- Questionnaire in English

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Faculty Opinions recommended

References

1. Abdullah A: The double burden of undernutrition and overnutrition in developing countries: an update. Curr Obes Rep. 2015; 4(3): 337–49. PubMed Abstract | Publisher Full Text
2. Wang Y, Lobstein T: Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes. 2006; 1(1): 11–25. PubMed Abstract | Publisher Full Text
3. Fazah A, Jacob C, Moussa E, et al.: Activity, inactivity and quality of life among Lebanese adolescents. Pediatr Int. 2010; 52(4): 573–8. PubMed Abstract | Publisher Full Text
4. Hu F: Obesity epidemiology. Oxford University Press; 2008. Publisher Full Text
5. Popkin BM, Adair LS, Ng SW: Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012; 70(1): 3–21. PubMed Abstract | Publisher Full Text | Free Full Text
6. Al-Nuaim AA, Al-Nakeeb Y, Lyons M, et al.: The prevalence of physical activity and sedentary behaviours relative to obesity among adolescents from Al-Ahsa, Saudi Arabia: rural versus urban variations. J Nutr Metab. 2012; 2012: 417589. PubMed Abstract | Publisher Full Text | Free Full Text
7. Binkley JK, Eales J, Jekanowski M: The relation between dietary change and rising US obesity. Int J Obes Relat Metab Disord. 2000; 24(8): 1032. PubMed Abstract | Publisher Full Text
8. Garcia G, Sunil TS, Hinojosa P: The fast food and obesity link: consumption patterns and severity of obesity. Obes Surg. 2012; 22(5): 810–8. PubMed Abstract | Publisher Full Text
9. Pereira MA, Kartashov AI, Ebbeling CB, et al.: Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet. 2005; 365(9453): 36–42. PubMed Abstract | Publisher Full Text
10. Duffey KJ, Gordon-Larsen P, Jacobs DR, et al.: Differential associations of fast food and restaurant food consumption with 3-y change in body mass index: the Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr. 2007; 85(1): 201–8. PubMed Abstract | Publisher Full Text
11. Scully M, Morley B, Niven P, et al.: Factors associated with high consumption of soft drinks among Australian secondary-school students. Public Health Nutr. 2017; 20(13): 2340–8. PubMed Abstract | Publisher Full Text
12. Scully M, Morley B, Niven P, et al.: Factors associated with high consumption of soft drinks among Australian secondary-school students. Public Health Nutr. 2017; 20(13): 2340–8. PubMed Abstract | Publisher Full Text
13. Kim SH, Hwang JY, Kim MK, et al.: Dietary factors related to body weight in adult Vietnamese in the rural area of Haiphong, Vietnam: the Korean Genome and Epidemiology Study (KoGES). Nutr Res Pract. 2010; 4(3): 235–42. PubMed Abstract | Publisher Full Text | Free Full Text
14. Mendez MA, Monteiro CA, Popkin BM: Overweight exceeds underweight among women in most developing countries. Am J Clin Nutr. 2005; 81(3): 714–21. PubMed Abstract | Publisher Full Text
15. Hsieh FY, Bloch DA, Larsen MD: A simple method of sample size calculation for linear and logistic regression. Stat Med. 1998; 17(14): 1623–34. PubMed Abstract | Publisher Full Text
16. Darebo T, Mesfin A, Gebremedhin S: Prevalence and factors associated with overweight and obesity among adults in Hawassa city, southern Ethiopia: a community based cross-sectional study. BMC Obes. 2019; 6(1): 8. PubMed Abstract | Publisher Full Text | Free Full Text
17. Ferreira-Pêgo C, Babio N, Bes-Rastrollo M, et al.: Frequent Consumption of Sugar- and Artificially Sweetened Beverages and Natural and Bottled Fruit Juices Is Associated with an Increased Risk of Metabolic Syndrome in a Mediterranean Population at High Cardiovascular Disease Risk. 2016; 146(8): 1528–36. Publisher Full Text
18. Kang Y, Kim J: Soft drink consumption is associated with increased incidence of the metabolic syndrome only in women. Br J Nutr. 2017; 117(2): 315–24. PubMed Abstract | Publisher Full Text
19. Casico: Market Analysis for fast food chain in Cambodia, Vietman, Loa and Myanmar. 2014. Reference Source
20. Singh GM, Micha R, Khatibzadeh S, et al.: Global, Regional, and National Consumption of Sugar-Sweetened Beverages, Fruit Juices, and Milk: A Systematic Assessment of Beverage Intake in 187 Countries. PLoS One. 2015; 10(8): e0124845. PubMed Abstract | Publisher Full Text | Free Full Text
21. Loh DA, Moy FM, Zaharan NL, et al.: Sugar-sweetened beverage intake and its associations with cardiometabolic risks among adolescents. Pediatr Obes. 2017; 12(1): e1–e5. PubMed Abstract | Publisher Full Text
22. Mendy VL, Vargas R, Payton M, et al.: Association Between Consumption of Sugar-Sweetened Beverages and Sociodemographic Characteristics Among Mississippi Adults. Prev Chronic Dis. 2017; 14: E137. PubMed Abstract | Publisher Full Text | Free Full Text
23. Barrett P, Imamura F, Brage S, et al.: Sociodemographic, lifestyle and behavioural factors associated with consumption of sweetened beverages among adults in Cambridgeshire, UK: the Fenland Study. Public Health Nutr. 2017; 20(15): 2766–77. PubMed Abstract | Publisher Full Text | Free Full Text
24. Pengpid S, Peltzer K: Prevalence and socio-behavioral factors associated with sugar-sweetened beverages consumption among 15 years and older persons in South Africa. Diabetes Metab Syndr Obes. 2019; 12: 937–45. PubMed Abstract | Publisher Full Text | Free Full Text
25. Samphors S, Pisey V, Dewey RS: Underlying Data 1. figshare. Dataset. 2020. http://www.doi.org/10.6084/m9.figshare.12612998.v1
26. Samphors S, Pisey V, Dewey RS: Extended Data. figshare. Dataset. 2020. http://www.doi.org/10.6084/m9.figshare.12612992.v1

Comments on this article Comments (0)

Version 3

VERSION 3 PUBLISHED 15 Jul 2020

Author details Author details

Wonga Laohasiriwong
Roles: Conceptualization, Methodology, Supervision, Validation

Pall Chamroen
Roles: Conceptualization, Project Administration, Resources, Writing – Review & Editing

Vong Pisey
Roles: Conceptualization, Methodology, Software, Validation, Visualization, Writing – Original Draft Preparation

Rebecca S. Dewey
Roles: Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (3)

version 3

Revised

Published: 09 Aug 2021, 9:708

https://doi.org/10.12688/f1000research.24890.3

version 2

Revised

Published: 28 Sep 2020, 9:708

https://doi.org/10.12688/f1000research.24890.2

version 1

Published: 15 Jul 2020, 9:708

https://doi.org/10.12688/f1000research.24890.1

© 2020 Laohasiriwong W 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 work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

SEE MORE DETAILS

CITE

how to cite this article

Laohasiriwong W, Samphors S, Chamroen P et al. Association between socioeconomic factors and soft drink consumption among adults in Cambodia: a cross-sectional study [version 2; peer review: 1 approved with reservations]. F1000Research 2020, 9:708 (https://doi.org/10.12688/f1000research.24890.2)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Version 2

VERSION 2

PUBLISHED 28 Sep 2020

Revised

Views

Reviewer Report 17 Jun 2021

Prince Atorkey, Priority Research Centre for Health Behaviour, School of Medicine and Public Health, University of Newcastle, Callaghan, Australia

Approved with Reservations

https://doi.org/10.5256/f1000research.29752.r84775

The aim of this study is to examine the association between socioeconomic factors and consumption of soft drinks among adults in consumption. The prevalence of soft drink consumption was 44.73%. Factors associated with soft drink consumption were male gender, age, ... Continue reading

I am not sure what the authors mean by "to fulfill their energy" in the abstract. I suggest they reword.
"confident interval" in the abstract should be confidence interval.
The second and third sentences in the introduction should be referenced.
How the random sampling was done at each stage should be specified.
For inclusion criteria, the authors stated "..and were able to understand the questionnaire." Please specify the language the questionnaires were in.
Why was diarrhea at the time of data collection an exclusion criteria?
In table 1, should >300 and > 500 be <300 and <500 instead?
The practical implications of the findings should be stated.
Limitations of the study should be stated.
The manuscript should be checked properly for grammar.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Health risk behaviours and mental health

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

Report a concern

Author Response 09 Aug 2021

Samphors Sim, Graduate School, Chea Sim University of Kamchaymear, Prey Veng, Cambodia

09 Aug 2021

Author Response
1. It has already been reworded.
2. It has already been edited.
3. It has already been added.
4. We use the lottery
... Continue reading
It has already been reworded.

It has already been edited.

It has already been added.

We use the lottery random sampling in every stage with random.

Khmer language is the native language of participants. In case the participants are not able to read the Khmer language, they are excluded.

Participants will not feel well for answering or responding the answer.

It has been corrected.

It has been added in the manuscript.

It has been added in the manuscript.

Checked.
It has already been reworded.

It has already been edited.

It has already been added.

We use the lottery random sampling in every stage with random.

Khmer language is the native language of participants. In case the participants are not able to read the Khmer language, they are excluded.

Participants will not feel well for answering or responding the answer.

It has been corrected.

It has been added in the manuscript.

It has been added in the manuscript.

Checked.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 09 Aug 2021

Samphors Sim, Graduate School, Chea Sim University of Kamchaymear, Prey Veng, Cambodia

09 Aug 2021

Author Response
1. It has already been reworded.
2. It has already been edited.
3. It has already been added.
4. We use the lottery
... Continue reading
It has already been reworded.

It has already been edited.

It has already been added.

We use the lottery random sampling in every stage with random.

Khmer language is the native language of participants. In case the participants are not able to read the Khmer language, they are excluded.

Participants will not feel well for answering or responding the answer.

It has been corrected.

It has been added in the manuscript.

It has been added in the manuscript.

Checked.
It has already been reworded.

It has already been edited.

It has already been added.

We use the lottery random sampling in every stage with random.

Khmer language is the native language of participants. In case the participants are not able to read the Khmer language, they are excluded.

Participants will not feel well for answering or responding the answer.

It has been corrected.

It has been added in the manuscript.

It has been added in the manuscript.

Checked.
Competing Interests: No competing interests were disclosed. Close
Report a concern

Comments on this article Comments (0)

Version 3

VERSION 3 PUBLISHED 15 Jul 2020

Open Peer Review

Reviewer Status

Reviewer Reports

	Invited Reviewers
	1
Version 3 (revision) 09 Aug 21
Version 2 (revision) 28 Sep 20	read
Version 1 15 Jul 20

Prince Atorkey, School of Medicine and Public Health, University of Newcastle, Callaghan, Australia

Comments on this article

All Comments(0)

Add a comment

Browse by related subjects

Back to all reports

Reviewer Report

21 Views

17 Jun 2021 | for Version 2

Prince Atorkey, Priority Research Centre for Health Behaviour, School of Medicine and Public Health, University of Newcastle, Callaghan, Australia

21 Views Cite this report Responses(1)

Approved With Reservations

I am not sure what the authors mean by "to fulfill their energy" in the abstract. I suggest they reword.
"confident interval" in the abstract should be confidence interval.
The second and third sentences in the introduction should be referenced.
How the random sampling was done at each stage should be specified.
For inclusion criteria, the authors stated "..and were able to understand the questionnaire." Please specify the language the questionnaires were in.
Why was diarrhea at the time of data collection an exclusion criteria?
In table 1, should >300 and > 500 be <300 and <500 instead?
The practical implications of the findings should be stated.
Limitations of the study should be stated.
The manuscript should be checked properly for grammar.

Is the work clearly and accurately presented and does it cite the current literature?

Partly
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

No
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Health risk behaviours and mental health

Respond to this report

Responses (1)

Author Response

09 Aug 2021

Samphors Sim, Graduate School, Chea Sim University of Kamchaymear, Prey Veng, Cambodia

It has already been reworded.
It has already been edited.
It has already been added.
We use the lottery random sampling in every stage with random.
Khmer language is the native language of participants. In case the participants are not able to read the Khmer language, they are excluded.
Participants will not feel well for answering or responding the answer.
It has been corrected.
It has been added in the manuscript.
It has been added in the manuscript.
Checked.

View more View less

Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. Abdullah A: The double burden of undernutrition and overnutrition in developing countries: an update. Curr Obes Rep. 2015; 4(3): 337–49. PubMed Abstract | Publisher Full Text

[2] 2. Wang Y, Lobstein T: Worldwide trends in childhood overweight and obesity. Int J Pediatr Obes. 2006; 1(1): 11–25. PubMed Abstract | Publisher Full Text

[3] 3. Fazah A, Jacob C, Moussa E, et al.: Activity, inactivity and quality of life among Lebanese adolescents. Pediatr Int. 2010; 52(4): 573–8. PubMed Abstract | Publisher Full Text

[4] 4. Hu F: Obesity epidemiology. Oxford University Press; 2008. Publisher Full Text

[5] 5. Popkin BM, Adair LS, Ng SW: Global nutrition transition and the pandemic of obesity in developing countries. Nutr Rev. 2012; 70(1): 3–21. PubMed Abstract | Publisher Full Text | Free Full Text

[6] 6. Al-Nuaim AA, Al-Nakeeb Y, Lyons M, et al.: The prevalence of physical activity and sedentary behaviours relative to obesity among adolescents from Al-Ahsa, Saudi Arabia: rural versus urban variations. J Nutr Metab. 2012; 2012: 417589. PubMed Abstract | Publisher Full Text | Free Full Text

[7] 7. Binkley JK, Eales J, Jekanowski M: The relation between dietary change and rising US obesity. Int J Obes Relat Metab Disord. 2000; 24(8): 1032. PubMed Abstract | Publisher Full Text

[8] 8. Garcia G, Sunil TS, Hinojosa P: The fast food and obesity link: consumption patterns and severity of obesity. Obes Surg. 2012; 22(5): 810–8. PubMed Abstract | Publisher Full Text

[9] 9. Pereira MA, Kartashov AI, Ebbeling CB, et al.: Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet. 2005; 365(9453): 36–42. PubMed Abstract | Publisher Full Text

[10] 10. Duffey KJ, Gordon-Larsen P, Jacobs DR, et al.: Differential associations of fast food and restaurant food consumption with 3-y change in body mass index: the Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr. 2007; 85(1): 201–8. PubMed Abstract | Publisher Full Text

[11] 11. Scully M, Morley B, Niven P, et al.: Factors associated with high consumption of soft drinks among Australian secondary-school students. Public Health Nutr. 2017; 20(13): 2340–8. PubMed Abstract | Publisher Full Text

[12] 12. Scully M, Morley B, Niven P, et al.: Factors associated with high consumption of soft drinks among Australian secondary-school students. Public Health Nutr. 2017; 20(13): 2340–8. PubMed Abstract | Publisher Full Text

[13] 13. Kim SH, Hwang JY, Kim MK, et al.: Dietary factors related to body weight in adult Vietnamese in the rural area of Haiphong, Vietnam: the Korean Genome and Epidemiology Study (KoGES). Nutr Res Pract. 2010; 4(3): 235–42. PubMed Abstract | Publisher Full Text | Free Full Text

[14] 14. Mendez MA, Monteiro CA, Popkin BM: Overweight exceeds underweight among women in most developing countries. Am J Clin Nutr. 2005; 81(3): 714–21. PubMed Abstract | Publisher Full Text

[15] 15. Hsieh FY, Bloch DA, Larsen MD: A simple method of sample size calculation for linear and logistic regression. Stat Med. 1998; 17(14): 1623–34. PubMed Abstract | Publisher Full Text

[16] 16. Darebo T, Mesfin A, Gebremedhin S: Prevalence and factors associated with overweight and obesity among adults in Hawassa city, southern Ethiopia: a community based cross-sectional study. BMC Obes. 2019; 6(1): 8. PubMed Abstract | Publisher Full Text | Free Full Text

[17] 17. Ferreira-Pêgo C, Babio N, Bes-Rastrollo M, et al.: Frequent Consumption of Sugar- and Artificially Sweetened Beverages and Natural and Bottled Fruit Juices Is Associated with an Increased Risk of Metabolic Syndrome in a Mediterranean Population at High Cardiovascular Disease Risk. 2016; 146(8): 1528–36. Publisher Full Text

[18] 18. Kang Y, Kim J: Soft drink consumption is associated with increased incidence of the metabolic syndrome only in women. Br J Nutr. 2017; 117(2): 315–24. PubMed Abstract | Publisher Full Text

[19] 19. Casico: Market Analysis for fast food chain in Cambodia, Vietman, Loa and Myanmar. 2014. Reference Source

[20] 20. Singh GM, Micha R, Khatibzadeh S, et al.: Global, Regional, and National Consumption of Sugar-Sweetened Beverages, Fruit Juices, and Milk: A Systematic Assessment of Beverage Intake in 187 Countries. PLoS One. 2015; 10(8): e0124845. PubMed Abstract | Publisher Full Text | Free Full Text

[21] 21. Loh DA, Moy FM, Zaharan NL, et al.: Sugar-sweetened beverage intake and its associations with cardiometabolic risks among adolescents. Pediatr Obes. 2017; 12(1): e1–e5. PubMed Abstract | Publisher Full Text

[22] 22. Mendy VL, Vargas R, Payton M, et al.: Association Between Consumption of Sugar-Sweetened Beverages and Sociodemographic Characteristics Among Mississippi Adults. Prev Chronic Dis. 2017; 14: E137. PubMed Abstract | Publisher Full Text | Free Full Text

[23] 23. Barrett P, Imamura F, Brage S, et al.: Sociodemographic, lifestyle and behavioural factors associated with consumption of sweetened beverages among adults in Cambridgeshire, UK: the Fenland Study. Public Health Nutr. 2017; 20(15): 2766–77. PubMed Abstract | Publisher Full Text | Free Full Text

[24] 24. Pengpid S, Peltzer K: Prevalence and socio-behavioral factors associated with sugar-sweetened beverages consumption among 15 years and older persons in South Africa. Diabetes Metab Syndr Obes. 2019; 12: 937–45. PubMed Abstract | Publisher Full Text | Free Full Text

[25] 25. Samphors S, Pisey V, Dewey RS: Underlying Data 1. figshare. Dataset. 2020. http://www.doi.org/10.6084/m9.figshare.12612998.v1

[26] 26. Samphors S, Pisey V, Dewey RS: Extended Data. figshare. Dataset. 2020. http://www.doi.org/10.6084/m9.figshare.12612992.v1

Association between socioeconomic factors and soft drink consumption among adults in Cambodia: a cross-sectional study

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Methods

Study setting and design

Study participants

Questionnaire

Statistical analysis

Results

Socioeconomic characteristics of the participants

Table 1. Baseline characteristics of respondents (n=749).

Factors associated with soft drink consumption with simple logistic regression

Table 2. Odds ratio (ORs) of socioeconomic factors associated with soft drink consumption (SDC) and their 95% confidence intervals (CIs) (n=749).

Factors associated with soft drink consumption with multiple logistic regressions

Table 3. Adjusted odds ratio (ORs) of socioeconomic factors associated with soft drink consumption (SDC) and their 95% confidence intervals (CIs) (n=749).

Discussion

Conclusion

Data availability

Underlying data

Extended data

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Reviewer Reports

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated