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Association between the frequency of television watching and overweight and obesity among women of reproductive age in Nepal: Analysis of data from the Nepal Demographic and Health Survey 2016

Association between the frequency of television watching and overweight and obesity among women

http://orcid.org/0000-0002-7680-676X

Das Gupta

Rajat

Conceptualization Data curation Formal analysis Investigation Methodology Project administration Writing – original draft Writing – review & editing ¹ ² ³ * Haider

Shams Shabab

Investigation Methodology Validation Visualization Writing – original draft ² Hashan

Mohammad Rashidul

Conceptualization Methodology Validation Visualization Writing – original draft ⁴ Hasan

Mehedi

Formal analysis Investigation Methodology Writing – review & editing ¹ ² Sutradhar

Ipsita

Conceptualization Investigation Methodology Writing – review & editing ¹ ² Sajal

Ibrahim Hossain

Conceptualization Investigation Writing – review & editing ² ⁵ Joshi

Hemraj

Formal analysis Methodology Validation Writing – review & editing ⁶ Haider

Mohammad Rifat

Conceptualization Investigation Supervision Writing – review & editing ⁷ Sarker

Malabika

Conceptualization Investigation Supervision Writing – review & editing ¹ ² ⁸

Centre for Non-Communicable Diseases and Nutrition, BRAC James P Grant School of Public Health, BRAC University, Mohakhali, Dhaka, Bangladesh

Centre for Science of Implementation & Scale Up, BRAC James P Grant School of Public Health, BRAC University, Mohakhali, Dhaka, Bangladesh

Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America

International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh

Department of Mathematical Sciences, School of Natural Sciences & Mathematics, The University of Texas at Dallas, Dallas, Texas, United States of America

Department of Public Health, Modern Technical College, Sanepa, Lalitpur, Nepal

Department of Social and Public Health, College of Health Sciences and Professions, Ohio University, Athens, Ohio, United States of America

Institute of Public Health, University of Heidelberg, Heidelberg, Germany

Gray

Cindy

Editor

University of Glasgow, UNITED KINGDOM

The authors have declared that no competing interests exist.

* E-mail: rajat89.dasgupta@gmail.com

10 2 2020

2020

15 2

e0228862

20 7 2019 25 1 2020

2020

Das Gupta et al

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Background

The prevalence of overweight and obesity, particularly among women, is increasing in Nepal. Previous studies in the South Asia have found television watching to be a risk factor for overweight and obesity among women of reproductive age. However, this association had not been studied in the context of Nepal. This study aims to identify the association between frequency of television watching and overweight and obesity among Nepalese women of reproductive age.

Methods

This cross-sectional study utilized the Nepal Demographic and Health Survey 2016 (NDHS 2016) data. A total weighted sample of 6,031 women were included in the final analyses. The women were 15–49 years of age and were either not pregnant or had not delivered a child within the two months prior to the survey. Body mass index (BMI) was the primary outcome of this study, which was categorized using an Asia-specific cutoff value. Normal and/or underweight was defined as a BMI <23.0 kg/m², overweight was defined as a BMI between 23.0 kg/m² and <27.5 kg/m², and obesity was defined as a BMI ≥27.5 kg/m². Frequency of watching television was the main independent variable of this study, which was divided into the following three categories: not watching television at all, watching television less than once a week, and watching television at least once a week. Multilevel ordered logistic regression was conducted to find the factors associated with overweight and obesity. A p-value <0.05 was considered significant in the final model.

Results

Around 35% of the participants were overweight or obese (overweight: 23.7% and obese: 11.6%). A majority of the study participants was aged between 15 and 24 years (36.5%), and resided in an urban area (63.2%), Province No. 3 (22.3%), and the Terai ecological region (49.5%). Around one-third (34.0%) of the participants received no formal education while an almost similar proportion (35.5%) completed secondary education. Approximately half of the study participants (50.6%) reported watching television at least once a week, whereas more than a quarter (28.7%) of them did not watch television at all. Women who watched television at least once a day had a higher prevalence of overweight and obesity than the other groups (p-value <0.0001). Women who watched television at least once a week were 1.3 times more likely to be overweight or obese in comparison to women who never watched television (Adjusted Odds Ratio (AOR): 1.3, 95% CI: 1.0–1.7; p-value <0.05). In the urban areas, women who watched television at least once a week were 40% more likely to be overweight or obese than those who did not watch television at all (AOR: 1.4, 95% CI: 1.1–1.7; p-value <0.01). No significant association between overweight and obesity and the frequency of viewing television was observed in the rural area.

Conclusions

Watching television at least once a week is associated with overweight and obesity in women of reproductive age living in the urban areas of Nepal. Public health promotion programs should raise awareness among women regarding harmful health consequences of sedentary lifestyle due to television watching.

The authors received no specific funding for this work.

Data Availability

The dataset of NDHS 2016 is available at the Demographic and Health Surveys Program. Extra data is available which is available on request at https://dhsprogram.com/What-We-Do/survey/survey-display-349.cfm.

Introduction

Overweight and obesity is an established risk factor for several non-communicable diseases (NCDs), including cardiovascular diseases, Type 2 diabetes mellitus, cancer, and chronic kidney disease [1,2]. According to the Global Burden of Disease 2017 study, overweight and obesity is the fourth leading cause of mortality around the world [3]. In addition, several complications for women of reproductive age, including pre-eclampsia, eclampsia, and gestational diabetes mellitus are associated with overweight and obesity [4,5]. The increasing burden of obesity has also emerged as a leading global public health problem. Overall, from the year 1975 to 2016, the number of men with obesity has increased from 31 million to 281 million (an approximately 800% absolute increase). During the same time period, the absolute number of women with obesity has increased by almost 465%, from 69 million to 390 million [6]. South and Southeast Asian countries, including Nepal, are facing an epidemiological transition with an increased burden of overweight and obesity [7]. In particular, the prevalence of overweight and obesity among Nepalese women of reproductive age (15–49 years) is increasing alarmingly [8].

Overweight and obesity results from an imbalance between energy intake and expenditure; high intake and low expenditure (i.e. inadequate physical activity) lead to weight gain and eventually overweight and obesity [9]. People spending their leisure time watching television tend to expend less energy, which predisposes them to gain excessive body weight [10]. It has also been reported that those who watch television are more frequently exposed to advertisements for foods and beverages and consequently tend to intake those foods and beverages more often, leading to an overall increased energy intake [11]. Association between an increased frequency of television watching and overweight and obesity has been reported in many high-income countries, including Australia and USA [12,13]. In Bangladesh, India, and Myanmar, the association between watching television at least once a week and overweight and obesity was identified in the case of women of reproductive age [14,15,16]. In the context of Nepal, this association has remained unexplored. This study aims to bridge the knowledge gap by investigating whether there is any association between frequency of television watching and overweight and obesity among Nepalese women of reproductive age. We used the nationally representative Nepal Demographic and Health Survey 2016 (NDHS 2016) data in this study.

Materials and methods Study setting

Nepal is a South Asian country with a population of 28.1 million people [17]. Geographically, Nepal is divided into three ecological regions: the Terai (lowlands), the Hills (snowless mountains), and the Mountains (snow-covered Himalayan mountains). The country was divided into five developmental regions and 75 districts before 2015 [18]. Following a federal reformation in 2015, the old developmental regions were replaced by seven new provinces comprised of 77 districts. The provinces were numbered No. 1 through No. 7. Only Province No. 2 and No. 5 do not have an example of all three ecological regions. Rather, they are both situated entirely in the Terai region. All of the provinces have rural and urban areas [19]. Previous studies have found a higher prevalence of overweight and obesity in Provinces No. 3 and No. 4 as well as in the Hilly region compared to other provinces and ecological regions, respectively [20,21]. It should be noted that some of the new provinces have received official names since this data was collected; however, in order to maintain continuity, this document will only refer to them by their original numbers.

Data source

A secondary analysis of the data obtained from the nationally representative cross-sectional NDHS 2016 was used for this study. The study was implemented in Nepal by NEW ERA between June 2016 and January 2017. NEW ERA is a non-profit, non-governmental research organization in Nepal. The Ministry of Health, Nepal (MoH) was responsible for overseeing the study [22]. For data collection, stratified random cluster sampling of households was followed. In the rural area, a two-stage stratified sampling technique was followed. During the first phase of data collection, a total of 199 primary sampling units (PSUs) were selected using the probability proportional to size method, followed by selection of households from the PSUs. In the urban area, a three-stage sampling procedure was followed [22]. First, 184 wards were selected as PSUs, followed by a random selection of enumeration areas (EAs) from each PSU. Then, the households were selected at the final stage of sampling. Final data was collected from 11,490 households (urban: 5,520 households and rural: 5,970 households). All women aged 15–49 years, both permanent and temporary residents of the household, were interviewed. The response rate of the survey was 96%. The detailed methodology of NDHS 2016 was published previously [22]. In this study, we analyzed the data from women of reproductive age (15–49 years), excluding data from women who were pregnant or had delivered within two months of the data collection.

Data collection and measurements

NDHS 2016 modified and adopted a standard woman’s questionnaire used by the Demographic and Health Survey (DHS) program according to the local context of Nepal to collect socio-demographic information (e.g. age; marital status; household wealth status; number of household members; place, province, and ecological region of residence; etc.). Interviews and anthropometric measurements were conducted by trained staff. Calibrated measuring boards and calibrated SECA scales were used for height and weight measurement, respectively.

Outcome variables and covariates

Body mass index (BMI) was the primary outcome of this study, which was categorized using an Asia-specific cutoff value [23]. This cutoff was used as advised by a World Health Organization (WHO) expert consultation group in order to account for differences in association between BMI and body fat with health risks when compared to the European population [23]. Normal and/or underweight was defined as a BMI <23.0 kg/m², overweight was defined as a BMI between 23.0 kg/m² and <27.5 kg/m², and obesity was defined as ≥27.5 kg/m².

Frequency of watching television was the main independent variable of this study, which was divided into the following three categories: (1) not watching television at all, (2) watching television less than once a week, and (3) watching television at least once a week [22]. The other covariates considered based on the literature review (which were found to be associated with overweight and obesity in previous studies) were age group [20], place of residence, province of residence [20], ecological region of residence [21], marital status [20], highest educational attainment [21], household wealth status [20], current employment status [24], parity [25], and number of household members in the family [26]. The categories of the covariates are mentioned in Table 1. The NDHS 2016 collected data on selected assets, such as construction material type used for the household, types of water source and sanitation facilities, electricity, and other belongings (e.g. television, bicycle, etc.). Principal component analysis was then conducted to measure household wealth index [22,27,28]. The wealth index was further divided into quintiles to generate household wealth status. In addition, the findings using a traditional BMI cutoff were compared to those using an Asian cutoff. In the traditional cutoff, normal and/or underweight was defined as a BMI <25.0 kg/m², overweight was defined as a BMI between 25.0 kg/m² and <30 kg/m², and obesity was defined as ≥30 kg/m² [29].

10.1371/journal.pone.0228862.t001

Table 1 List of variables considered for the study.

Study Variables	Description and Categories
Outcome Variable	BMI of the study paticipants as measured in kg/m²(0 = <23kg/m²; 1 = BMI 23-<27.5 kg/m²; 2 = ≥27.5kg/m²)
Explanatory Variables
Age	Age in years(0 = 15–24 years; 1 = 25–34 years; 2 = 35–49 years)
Place of Residence	Type of the cluster(0 = urban; 1 = rural)
Province of Residence	Province of residence(0 = Province No. 1; 1 = Province No. 2; 2 = Province No. 3; 3 = Province No. 4; 4 = Province No. 5; 5 = Province No. 6; 6 = Province No. 7)
Ecological Region of Residence	Topological region of residence(0 = Mountains; 1 = Hills; 2 = The Terai (Plains)
Education	Education level(0 = no formal education; 1 = primary; 2 = secondary; 3 = higher)
Household Wealth Status	Household wealth quintile(0 = poorest; 1 = poorer; 2 = middle; 3 = richer; 4 = richest)
Currently Employed	Current employment status(0 = no; 1 = yes)
Marital Status	Marital status(0 = single; 1 = married; 2 = separated/divorced/widowed)
Parity	Number of pregnancies reaching viable gestational age (including live births and stillbirths)(0 = 0; 1 = 1; 2 = 2; 3 = 3; 4 = 3+)
Number of Household Members	Number of members residing in the household(0 = ≤5; 1 = >5)
Frequency of Watching Television	Usual frequency of watching television(0 = Not at all; 1 = Less than once a week; 2 = At least once a week)

Data analysis

At first, descriptive weighted analyses were conducted to determine the socio-demographic characteristics of the study participants and were reported in frequency and percentage. To identify differences of the covariates according to the BMI status, chi-squared (χ²) tests were performed as part of the bivariate analyses. In the multivariable analysis, ordered logistic regression was conducted to find the factors associated with overweight and obesity. Multilevel regression was done considering the hierarchical nature of the NDHS 2016 data [30–32]. Variables that yielded a p-value <0.20 in the bivariate analyses were put in the multivariable model. This predefined p-value <0.20 was considered sufficient to avoid residual confounding in multivariable analyses [33]. A p-value <0.05 was considered significant in the multivariable model. Both the unadjusted Crude Odd Ratio (COR) and Adjusted Odds Ratio (AOR) with a 95% confidence interval (CI) were reported to show the strength of the association. To determine any multicollinearity among the covariates, the variance inflation factor (VIF) was tested. A VIF value greater than five was considered an indication of multicollinearity [34]. A significant interaction effect between the frequency of television viewing and the place of residence was observed and the interaction variable was included in the multivariable analyses. All the analyses were done in Stata 14.0. The authors followed the guidelines outlined in the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement in conducting this study and writing the manuscript [35].

Ethics approval

The NDHS 2016 protocol was reviewed and approved by the ethical review board of the Nepal Research Council as well as the institutional review board of ICF International. Written informed consent was taken from the head of the households and the study participants before data collection. The DHS program provided permission and access to the dataset for this study in February 2019.

Results

In the final analysis, data from 6,031 weighted samples were included. The sample selection for final analysis is shown in Fig 1. Around 35% of the participants were overweight or obese [overweight: 23.7% (95% CI: 22.4%-25.0%) and obese: 11.6% (95% CI: 10.2%-13.1%)].

10.1371/journal.pone.0228862.g001

Fig 1 Steps of sample selection in the final analysis.

The socio-demographic characteristics of the study participants are presented in Table 2. The majority of women were between 15 and 24 years of age (36.5%) and resided in an urban area (63.2%), Province No. 3 (22.3%), and the Terai region (49.5%). Around one-third (34.0%) of the participants did not receive any formal education, while an almost similar proportion (35.5%) completed secondary education. Around three-fifths of them were employed at the time of the survey (58.9%) and had fewer than or equal to five members in their household (61.8%). The highest proportion of them belonged to the richer wealth quintile (22.6%); however, around 36% of the study participants belonged to the lowest two wealth quintiles. More than a quarter (28.7%) of the study participants were nulliparous, while 19.2% had a parity of more than three. Around half of the women (50.6%) reported watching television at least once a week, whereas more than one-fourth (28.7%) of them did not watch television at all.

10.1371/journal.pone.0228862.t002

Table 2 Prevalence of overweight and obesity in the sample population across the explanatory variables, NDHS 2016.

Variable	n	%	BMI Status (%) in kg/m²
Variable	n	%	BMI <23	23≥ BMI <27.5	BMI ≥27.5
Age Group (years)***
15–24	2199	36.5	83.0	14.5	2.6
25–34	1834	30.4	58.0	27.9	14.1
35–49	1998	33.1	50.8	29.9	19.3
Place of Residence***
Urban	3814	63.2	60.4	24.9	14.7
Rural	2217	36.8	72.2	21.5	6.3
Province of Residence***
Province No. 1	1022	17.0	60.1	25.8	14.1
Province No. 2	1162	19.3	80.0	14.5	5.5
Province No. 3	1345	22.3	50.0	29.8	20.3
Province No. 4	604	10.0	51.6	31.9	16.4
Province No. 5	1023	16.9	66.9	24.4	8.6
Province No. 6	343	5.7	76.5	19.7	3.8
Province No. 7	532	8.8	80.6	15.8	3.6
Ecological Region of Residence***
Mountain	361	6.0	65.2	25.6	9.3
Hill	2687	44.6	58.7	26.5	14.8
The Terai	2983	49.5	70.1	20.9	9.0
Highest Educational Status***
No Formal Education	2050	34.0	67.1	23.2	9.7
Primary	980	16.3	57.7	27.6	14.7
Secondary	2141	35.5	67.3	21.6	11.2
Higher	860	14.3	60.8	25.5	13.8
Currently Employed*
Yes	3552	58.9	62.7	25.3	12.0
No	2479	41.1	67.6	21.3	11.1
Household Wealth Status ***
Poorest	1024	17.0	76.6	20.4	3.0
Poorer	1142	18.9	71.6	22.0	6.4
Middle	1221	20.2	73.1	20.5	6.5
Richer	1363	22.6	63.8	24.3	11.9
Richest	1281	21.2	42.1	30.1	27.7
Marital Status***
Single	1340	22.2	85.2	12.6	2.2
Currently Married	4514	74.9	59.0	26.5	14.5
Separated/Divorced/Widowed	177	2.9	55.7	34.9	9.4
Parity***
0	1733	28.7	81.6	14.6	3.8
1	888	14.7	63.3	23.9	12.8
2	1335	22.1	49.5	31.3	19.2
3	919	15.2	56.7	27.0	16.3
>3	1156	19.2	64.6	25.6	9.8
Number of Household Members***
≤5	3728	61.8	60.8	26.0	13.2
>5	2303	38.2	71.0	19.9	9.1
Frequency of Watching Television***
Not at all	1730	28.7	75.8	18.9	5.3
Less than once a week	1250	20.7	69.5	22.6	7.9
At least once a week	3051	50.6	56.5	26.8	16.7

NDHS: Nepal Demographic and Health Survey

*p-value <0.05,

**p-value <0.01,

*** p-value <0.001, derived from chi-square test.

The proportion of study participants who watched television at least once a week was significantly higher in the urban area compared to the rural area (urban: 60.0% vs. rural: 34.5%, p-value <0.0001).

Significant differences were found among the BMI of women across all the covariates. The prevalence of overweight and obesity was highest among women aged 35–49 years (p-value <0.001), residing in Province No. 3 (p-value <0.001), and in the Hill region (p-value <0.001). Urban areas had a higher prevalence of overweight and obesity compared to rural areas (overweight: urban 24.9% vs. rural 21.5%; obesity: urban 14.7% vs. rural 6.3%; p-value <0.001). Women who attained primary education only had the highest prevalence of overweight and obesity (p-value <0.001). The prevalence of overweight and obesity significantly increased with wealth index and nearly three-fifths of the women from the richest quintiles were overweight (30.1%) or obese (27.7%). Plausibly, women who watched television at least once a day had a higher prevalence of overweight and obesity than other groups (p-value <0.0001) (Table 2).

In the ordered logistic regression model, the normal weight category (BMI <23 kg/m²) was held as the reference group. In the final multivariable model, after adjusting for age, place and region of residence, wealth index, highest educational status, current employment status, parity, and number of household members, it was found that urban women who watched television at least once a week were 40% more likely to be overweight or obese than those who did not watch television at all (AOR: 1.4, 95% CI: 1.1–1.7; p-value <0.01). Conversely, no significant association between overweight and obesity and the frequency of watching television was observed among rural women. Overall, women who watched television at least once a week were 1.3 times more likely to be overweight or obese in comparison to women who never watched television (AOR: 1.3, 95% CI: 1.0–1.7; p-value <0.05). (Table 3). The detailed logistic regression models are shown in Supplementary Table 1–3 (S1 File). Logistic regression using a traditional BMI cutoff also revealed the same findings (S1 File). No significant multicollinearity was observed in the final model.

10.1371/journal.pone.0228862.t003

Table 3 Association between the frequency of watching television and overweight and obesity among reproductive age women in Nepal, NDHS 2016.

Frequency of Watching Television	COR (95% CI)	AOR (95% CI)
In Urban Area:
Not at all	Ref	Ref
Less than once a week	1.1 (0.9–1.4)	1.1 (0.8–1.4)
At least once a week	1.8*** (1.5–2.2)	1.4** (1.1–1.7)
In Rural Area:
Not at all	Ref	Ref
Less than once a week	1.0 (0.8–1.3)	1.0 (0.7–1.3)
At least once a week	1.4** (1.1–1.9)	1.1(0.8–1.5)
Total:
Not at all	Ref	Ref
Less than once a week	1.1(0.9–1.3)	1.2 (0.9–1.5)
At least once a week	1.7***(1.5–2.0)	1.3* (1.0–1.7)

NDHS: Nepal Demographic and Health Survey

COR: Crude Odds Ratio

CI: Confidence Interval

AOR: Adjusted Odds Ratio

*p-value<0.05,

**p-value<0.01,

***p-value<0.001

Results are based on ordered logistic regression and adjusted for age, place of residence, province of residence, ecological region of residence, highest educational status, current employment status, wealth index, parity, and number of household members. The BMI <23 kg/m² group was held as the reference group.

Discussion

To the best of our knowledge, this is the first study from Nepal that has investigated the association between frequency of television watching and overweight and obesity in women of reproductive age using a nationally representative sample. The study found that in the case of urban Nepalese women, those who watched television at least once a week were more likely to be overweight and obese compared to those who did not watch at all. This association was not statistically significant among rural women.

The study found that roughly one in three women (35%) of reproductive age in Nepal were either overweight or obese. This is almost similar to the prevalence of overweight and obesity (measured using the Asia-specific cutoff and a nationally representative sample) among women of reproductive age in neighboring South Asian countries, including Bangladesh (36%), Pakistan (39%), and Myanmar (38.7%) [16,36,37]. The prevalence of overweight and obesity was higher among women who were older, residing in Province No. 3, residing in the Hill region, were educated up to the primary level, and belonged to the richest wealth quintiles. All of these findings are consistent with previous studies conducted in Nepal and in neighboring India and Pakistan [14,38,39]. In general, the prevalence of overweight and obesity was found to be higher among urban women compared to rural women, which is also consistent with findings from earlier studies conducted in Nepal and other South Asian countries [16,36,21]. It was also found that the frequency of watching television at least once a week is higher among urban women compared to rural women. Similar findings were also made in Bangladesh and Myanmar [14,16]. Potential explanations for this phenomenon include a higher and more stable coverage of electricity, as well as the availability of more diverse satellite television channels [15.16].

The current study found a positive association between watching television once a week and overweight and obesity among women of reproductive age, which is consistent with findings from Bangladesh and Myanmar [14,16]. A study of Nepalese adolescents found that watching television more than two hours per day increased the risk of becoming overweight by nine times compared to those who watched television less than two hours a day [39]. Similar associations were observed in Western countries, such as Australia and the United States [12,13], as well as in Asian countries, such as Iran and China [11,40]. In this study, the association between watching television once a week and overweight and obesity was significant in the urban area, but not in the rural area. This was due to the overall higher frequency of television watching in the urban area. Watching television replaces time for physical activity and thus predisposes any person towards a sedentary lifestyle [41]. Furthermore, advertisements for energy-dense and unhealthy foods are more effective on and more likely to reach those watching television for longer. This increases their probability of purchasing and consuming the advertised obesogenic foods, which combined with an already sedentary lifestyle, increases the risk of being overweight or obese [13]. A recent study found that around 25% of the advertisements broadcast in Indian and Nepalese television are for junk food [42]. The availability and accessibility of fast food chains, restaurants, and shopping malls promoting junk food is higher in urban areas [43]. Moreover, there is increased compulsory physical activity for rural people due to the often less developed transportation systems and the increased involvement in manual labor [14]. This may be one reason that watching television at least once a week was not found to be significantly associated with overweight and obesity among rural women.

The higher burden of overweight and obesity is a public health problem in Nepal, which plays a role in the increasing burden of NCDs in the country. Currently, nearly three-fifths of the total disease burden is attributable to NCDs [44]. The health system of Nepal is more focused on curative measures, rather than preventive measures [44]. Preventive programs should be strengthened in order to reduce the burden of overweight and obesity and thus ultimately reducing the overall burden of NCDs. Health promotion programs focusing on women of reproductive age should incorporate the importance of physical activity and less ‘sitting time’ for television watching, especially in the urban area. Future research should use a nationally representative sample to assess whether this association exists in men and adolescents.

This study has several strengths. First, a nationally representative sample was used for this study and therefore the findings of this study are generalizable to the target population. Second, the response rate of this study was high (96%). Third, NDHS 2016 utilized validated questionnaires, calibrated measurement tools, and highly trained data collectors, all of which limited the possibility of measurement error. However, the study had some limitations as well. Due to the cross-sectional nature of the survey, we cannot draw a causal relationship between the frequency of television watching with overweight and obesity. Further, the data on frequency of television watching was collected on a scale of weeks, rather than hours or days, which limited our scope for further comprehensive or nuanced analysis. NDHS 2016 also did not collect data on physical activity level, dietary habits, or frequency of using other devices like computers and cellphones, hindering the inclusion of those possible covariates in our analyses.

Conclusion

The high burden of overweight and obesity in Nepal is a public health problem that warrants immediate action. This study identified that watching television at least once a week is associated with overweight and obesity in women of reproductive age living in urban areas of Nepal. Public health promotion programs in Nepal should make people aware of the adverse effects of frequent television watching.

Supporting information

S1 File Supplementary tables.

(PDF)

We are grateful to the DHS program for providing access to the dataset.

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10.1371/journal.pone.0228862.r001

Decision Letter 0

Gray

Cindy

Academic Editor

2020

Cindy Gray

Submission Version

22 Oct 2019

PONE-D-19-20505

Association between the frequency of television watching and overweight and obesity among women of reproductive age in Nepal: Analysis of data from the Nepal Demographic and Health Survey 2016

PLOS ONE

Dear Dr. Das Gupta,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’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.

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Cindy Gray, Ph.D.

Academic Editor

PLOS ONE

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Additional Editor Comments (if provided):

In general, the manuscript needs some careful reading to improve use of English, which is pretty good, but nevertheless there are some errors (e.g. overuse of ‘the’).

Abstract In general, the method needs to be more concise (e.g. need to summarise, not list covariates here), also you need to mention the co-variates in the results.

Introduction

ln 74: give % increase for men. Otherwise fine

Method

Ln 105: is there a reference for the probability proportional to size method?

Ln 133: what are ' 'The categories''? this needs more explanation

Ln 130: it is not clear how the literature review led to identification of the co-variates

Ln 133-135: why are the selected assets relevant to this study?

Results

I don’t think just reporting the highest value in each category gives a clear picture of the sample

Figures not clear

Ln 192-194: it is not meaningful to the reader to discuss Province No 3 and the Hill region without more description of context.

Think about how best to present your results to make them coherent e.g. urban vs rual might go first?

Discussion

p 238 Province and Hill need more explanation/context as before.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

**********

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: Yes

**********

5. 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 #1: ASSOCIATION BETWEEN THE FREQUENCY OF TELEVISION WATCHING AND OVERWEIGHT AND OBESITY AMONG WOMEN OF REPRODUCTIVE AGE IN NEPAL: ANALYSIS OF DATA FROM THE NEPAL DEMOGRAPHIC AND HEALTH SURVET 2016

OVERALL COMMENT:

This manuscript looks for the association between TV watching and overweight and obesity. The finding is not novel and several previous papers have shown such association in LMIC and Asian countries. Moreover, there is a concern related to the use of ordered logistic regression as the model to look for the association of interest, instead of using multinomial logistic regression. Such concern is increased as OR usually overestimates strength of the association when the outcome is highly prevalent (more than 10%) as in the case of overweight or obesity. A potential option would be to use prevalence ratios, but in this case using two different models (i.e. comparing overweight vs. normal and obesity vs. normal). Finally, why the authors use Asian cut-offs for BMI is not well explained. Ideally, I would like to see the association with traditional BMI cut-off as sensitivity analysis.

MAJOR COMMENTS:

Abstract:

- The direction of the association is capital here... is that obese women are more prone to watch TV? Or is that watching TV associated with overweight/obesity? Please define appropriately in the abstract.

- Reasons for using Asian BMI cut-offs should be clearly explained as they are not the usual cut-offs... in addition, please include sensitivity analysis using traditional cut-offs

- What proportion of people watchs TV at least once a week? Is that proportion important?

Introduction:

- Please define appropriately the direction of the association of interest throughout the text.

Methods:

- Line 102: randomized sampling or random sampling? This is not a trial.

- How the individual was selected for the study? Were all the women from household selected? Only one? Please explain.

- Line 118: Is it sex a variable? But all are women or not?

- Line 124: Reasons for using Asian BMI cut-offs should be detailed... In addition, a sensitivity analysis is needed to compare results with traditional cut-offs

- Not sure if ordered logistic regression is the best way to create the model to look for the association of interest, instead of using multinomial logistic regression for example. Such concern is increased as OR usually overestimates strength of the association when the outcome is highly prevalent (more than 10%) as in the case of overweight or obesity. A potential option should be to use prevalence ratios, but in this case using two different models (i.e. comparing overweight vs. normal and obesity vs. normal).

- Line 147-148: This is an exploratory model looking for potential variables independently associated with an outcome; but according to the objectives the idea sounds more like a confirmatory model (when you show your crude model and then the adjusted model controlling for potential confounders)

- Line 155: re collinearity: sounds like a result more than a part of the methods.

- Line 155-157: how interaction was assessed?

Findings

- Line 168: How the number 6031 was obtained? A flowchart may be useful here instead of the pie figure (this does not give more information than text).

- A sensitivity analysis is needed using traditional BMI cut-offs instead of Asian cut-offs... is the association found the same? Is it significant?

Discussion

- Please discuss about the relevance of the findings... how are they important for the public health perspective?

**********

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Reviewer #1: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

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10.1371/journal.pone.0228862.r002

Author response to Decision Letter 0

Submission Version

3 Nov 2019

Submitted Title: Association between the frequency of television watching and overweight and obesity among women of reproductive age in Nepal: Analysis of data from the Nepal Demographic and Health Survey 2016

Reference No: PONE-D-19-20505

Additional Editor Comments (if provided):

In general, the manuscript needs some careful reading to improve use of English, which is pretty good, but nevertheless there are some errors (e.g. overuse of ‘the’).

Response: Thanks! We have revised the manuscript. The language of the manuscript was further edited by an in-house editor who is a native English speaker.

Abstract In general, the method needs to be more concise (e.g. need to summarise, not list covariates here), also you need to mention the co-variates in the results.

Response: Thanks for this important comment! We have removed the list of covariates from the abstract. We have also added the summary of the covariates in the results.

Introduction

ln 74: give % increase for men. Otherwise fine

Response: Thanks! We have added the percentage increase for men as per suggestion.

Method

Ln 105: is there a reference for the probability proportional to size method?

Response: Thanks! We have added the reference. It is the Nepal Demographic and Health Survey 2016 report.

Ln 133: what are ' 'The categories''? this needs more explanation

Response: Thanks! We have revised the sentence: “The categories of the covariates are mentioned in Table 1.”

Ln 130: it is not clear how the literature review led to identification of the co-variates

Response: Thanks! In previous studies these covariates were found to be associated with overweight and obesity. So we have included them in the analysis. We have mentioned that in the revised manuscript and have added the reference.

Ln 133-135: why are the selected assets relevant to this study?

Response: Thanks! The selected assets were used to generate household wealth index which was then divided into quintiles to generate household wealth status, which is a covariate in our study. We have revised that paragraph as following: “The NDHS 2016 collected data on selected assets, such as household construction materials, types of water source and sanitation facilities, electricity and other belongings (e.g., television, bicycle, etc.). Principal component analysis was then conducted to measure household wealth index [16,18,19]. The wealth index was further divided into quintiles to generate household wealth status.”

Results

I don’t think just reporting the highest value in each category gives a clear picture of the sample

Response: Thanks! We have added additional information.

Figures not clear

Response: Thanks! We have removed both the figures.

Ln 192-194: it is not meaningful to the reader to discuss Province No 3 and the Hill region without more description of context.

Response: Thanks! We have added a paragraph called study settings under methods section where we discussed about the context including province and ecologic zone.

Think about how best to present your results to make them coherent e.g. urban vs rual might go first?

Response: Thanks! We have reorganized the findings. First we presented the odds ratio in the urban area, then rural area. At last we presented the overall odds ratio.

Discussion

p 238 Province and Hill need more explanation/context as before.

Response: Thanks! We have added a paragraph called study settings under methods section where we discussed about the context including province and ecologic zone.

OVERALL COMMENT:

Response: Many thanks for the comments. Thanks for this important suggestion. However, we believe that ordered logistic regression is the best way, because the outcome variable is an ordinal variable. Previous studies from this region also used ordered logistic regression.

India: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221758

Myanmar: https://bmjopen.bmj.com/content/9/3/e024680

Thanks! We have added the reason for using Asian BMI cut-offs: “Asia-specific cutoff was used because it was advised by the World Health Organization (WHO) expert consultation group, due to different associations BMI, body fat with health risks compared to the European population [17].” We have also added analysis the traditional cut-offs, which reveal similar findings like the Asian cut off.

MAJOR COMMENTS:

Abstract:

Response: Thanks for this comment. We have edited accordingly.

- Reasons for using Asian BMI cut-offs should be clearly explained as they are not the usual cut-offs... in addition, please include sensitivity analysis using traditional cut-offs

Response: Thanks! We have added the reason for using Asian BMI cut-offs: “Asia-specific cutoff was used because it was advised by the World Health Organization (WHO) expert consultation group, due to different associations BMI, body fat with health risks compared to the European population [17].” We have also added analysis the traditional cut-offs.

- What proportion of people watchs TV at least once a week? Is that proportion important?

Response: Thanks! We have mention in the findings section: “Around half of the respondents (50.6%) reported watching television at least once a week, whereas more than one-fourth (28.7%) of them watched television not at all.

The proportion of television watchers at least once a week was significantly higher in the urban area compared to the rural area (urban: 60.0% vs. rural: 34.5%, p-value<0.0001).” This proportion is important to understand the basic demographic characteristics of the respondents.

Introduction:

- Please define appropriately the direction of the association of interest throughout the text.

Response: Thanks for this comment. We have edited accordingly.

Methods:

- Line 102: randomized sampling or random sampling? This is not a trial.

Response: Thanks! We have edited it to random sampling.

- How the individual was selected for the study? Were all the women from household selected? Only one? Please explain.

Response: Thanks! We have added a sentence: “All women aged 15-49 years, who were either the permanent residents of the households or stayed at the household night before the survey were interviewed.”

- Line 118: Is it sex a variable? But all are women or not?

Response: Thanks! We have deleted the word ‘sex’.

- Line 124: Reasons for using Asian BMI cut-offs should be detailed... In addition, a sensitivity analysis is needed to compare results with traditional cut-offs

Response: Thanks for this important suggestion. However, we believe that ordered logistic regression is the best way, because the outcome variable is an ordinal variable. Previous studies from this region also used ordered logistic regression.

India: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221758

Myanmar: https://bmjopen.bmj.com/content/9/3/e024680

Response: Thanks for this comment.

- Line 155: re collinearity: sounds like a result more than a part of the methods.

Response: Thanks! We the statement in the findings section.

- Line 155-157: how interaction was assessed?

Response: We have shown the interaction in Model 2 under the supplementary file 1.

Findings

- Line 168: How the number 6031 was obtained? A flowchart may be useful here instead of the pie figure (this does not give more information than text).

Response: Thanks! we have added a flow chart (Figure 1).

- A sensitivity analysis is needed using traditional BMI cut-offs instead of Asian cut-offs... is the association found the same? Is it significant?

Response: Thanks! We have added analysis the traditional cut-offs.

Discussion

- Please discuss about the relevance of the findings... how are they important for the public health perspective?

Response: Thanks! We have mentioned this in the discussion section: “The higher burden of overweight and obesity is a public health problem in Nepal, which plays a role in the increasing burden of NCDs in the country. Currently, nearly three-fifths of the total disease burden is attributable to NCDs [35]. The health system of Nepal is more focused on the curative aspects of NCDs, rather than the preventive side [35]. Preventive programs should be strengthened in order to reduce the burden of overweight and obesity and thus ultimately reducing the overall burden of NCDs. Health promotion programs focusing on women of reproductive age should incorporate the importance of physical activity and less ‘sitting time’ for television watching, especially in the urban area. Future research should also include men and adolescents using a nationally representative sample to assess whether this association exists in those populations.”

Attachment

Submitted filename: Response to Reviewers.docx

10.1371/journal.pone.0228862.r003

Decision Letter 1

Gray

Cindy

Academic Editor

2020

Cindy Gray

Submission Version

20 Jan 2020

PONE-D-19-20505R1

Association between the frequency of television watching and overweight and obesity among women of reproductive age in Nepal: Analysis of data from the Nepal Demographic and Health Survey 2016

PLOS ONE

Dear Dr. Das Gupta,

We would appreciate receiving your revised manuscript by Mar 05 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Cindy Gray, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

The manuscript is looking good now. Just some very minor points to attend to

Abstract

ln 33 could “in the South Asian setting” just be “in South Asia”?

Ln 54 to 55 – should it read “A majority of the study participants was aged between 15 and 24 years (36.5%), AND resided in an urban area (63.2%), Province No. 3 (22.3%), and the Terai ecological region (49.5%).”

Ln 55-56 tense is wrong

Ln 58 one fourth should be a quarter

Introduction

Ln 84-85 “During the same time period, the global prevalence of women with obesity has increased by almost 465%, from 69 million to 390 million [6]” Edit suggested

Ln 105 (NDHS) 2016 does not align with the abstract (NDHS 2016) and elsewhere. Please make use of acronyms consistent

Method

Ln 108 Title should be Study Setting

Ln 125 – who are NEW ERA please describe

Ln 142-143 to collect socio-demographic information Edit suggested

Ln 145 SECA scales needs more information e.g. manufacturer

Ln 168 the findings using a traditional BMI cutoff were Edit suggested

In table 1 – I don’t think you need to keep repeating of the respondents or of the study participants? Also please be consistent don’t call them respondents and participants

Ln 181 NDHS 2016 data – be consistent

Ln 196 The NDHS 2016 edit suggested. Also is it one or two boards – please make this clear

Findings

ln 208 “were” is missing

Ln 210 should this be and/or the Tari region

Ln 213 should be had fewer than

Ln 215 a quarter

Please be consistent – are they respondents or study participants? Also you don’t need to keep repeating this

Ln 232-235 Women who attained primary education only had the highest prevalence of overweight and obesity (p-value <0.001). The prevalence of overweight and obesity significantly increased with wealth index and nearly three-fifths of the women from the richest quintiles were overweight (30.1%) or obese (27.7%). THIS SEEMS COUNTERINTUITIVE – DO YOU DISCUSS IT? (I would have thought wealthy women would be better educated?) Also is it not coherent with the discussion which says (ln274-276 The prevalence of overweight and obesity was higher among women who were older, residing in Province No. 3, residing in the Hill region, had higher educational attainment, and belonged to the richest wealth quintiles.

Discussion

Ln 264 between frequency of television Suggested edit

Ln 270 Nepal were either Suggested edit

Ln 288 A study of Nepalese Suggested edit

Ln 291 in Western countries Suggested edit

Ln 292-293 In this study, the association between watching television once a week and overweight and obesity was significant in the urban area, but not in the rural area. Suggested edit

Ln 304 This may be one reason Suggested edit

Ln 309 – should you spell out non-communicable diseases the first time?

Ln 318-319 . First, a nationally representative sample was used for this study and therefore the findings of this study are generalizable to the target population. Suggested edit

Conclusion

Ln 331 The high burden of overweight and obesity in Nepal is a public health problem that warrants immediate action. Suggested edit

Ln 333 age living in urban areas Suggested edit

Check the Figure – there is a line spacing issue in the second last box

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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 #1: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: No

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

Reviewer #1: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

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

Reviewer #1: Yes

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6. Review Comments to the Author

Reviewer #1: All the comments have been addressed. However, two minor points appear:

- Introduction: line 85, 69 million or 390 million are not prevalence as stated, they are absolute numbers.

- Outcome variables and covariates: line 170: should be "and <30 kg/m2" to avoid overlap with the obesity category.

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Reviewer #1: No

10.1371/journal.pone.0228862.r004

Author response to Decision Letter 1

Submission Version

20 Jan 2020

Manuscript ID: PONE-D-19-20505R1

Additional Editor Comments (if provided):

The manuscript is looking good now. Just some very minor points to attend to

Abstract

ln 33 could “in the South Asian setting” just be “in South Asia”?