Individual and community-level determinants of overweight and obesity among urban men: Further analysis of the Ethiopian demographic and health survey

Tekalegn, Yohannes; Engida, Zinash Teferu; Sahiledengle, Biniyam; Rogers, Heather; Seyoum, Kenbon; Woldeyohannes, Demelash; Legese, Birhan; Ayele, Tadesse Awoke

doi:10.1371/journal.pone.0259412

Cited by 8 publications

(11 citation statements)

References 47 publications

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“…We also noted that physical activity was a predictor of obesity in all island clusters. This result was consistent with many prior studies conducted in Indonesia and elsewhere that reported that a lack of physical activity is strongly associated with obesity [ 34 , 35 , 36 , 37 , 38 , 39 ]. Performing sufficient physical activity might be beneficial to maintain people’s energy expenditure and subsequent energy balance.…”

Section: Discussionsupporting

confidence: 93%

“…Meanwhile, in the Sulawesi Island cluster and other island clusters outside the Java cluster, the number and distribution of urban communities is relatively fewer and uneven. A similar finding was reported by a study in Ethiopia that found that men living in metropolitan cities were 1.8 times more likely to become obese than those living in rural areas [36].…”

Section: Discussionsupporting

confidence: 88%

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Obesity Risk-Factor Variation Based on Island Clusters: A Secondary Analysis of Indonesian Basic Health Research 2018

et al. 2022

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Obesity has become a rising global health problem affecting quality of life for adults. The objective of this study is to describe the prevalence of obesity in Indonesian adults based on the cluster of islands. The study also aims to identify the risk factors of obesity in each island cluster. This study analyzes the secondary data of Indonesian Basic Health Research 2018. Data for this analysis comprised 618,910 adults (≥18 years) randomly selected, proportionate to the population size throughout Indonesia. We included 20 variables for the socio-demographic and obesity-related risk factors for analysis. The obesity status was defined using Body Mass Index (BMI) ≥ 25 kg/m2. Our current study defines 7 major island clusters as the unit analysis consisting of 34 provinces in Indonesia. Descriptive analysis was conducted to determine the characteristics of the population and to calculate the prevalence of obesity within the provinces in each of the island clusters. Multivariate logistic regression analyses to calculate the odds ratios (ORs) was performed using R version 3.6.3. The study results show that all the island clusters have at least one province with an obesity prevalence above the national prevalence (35.4%). Six out of twenty variables, comprising four dietary factors (the consumption of sweet food, high-salt food, meat, and carbonated drinks) and one psychological factor (mental health disorders), varied across the island clusters. In conclusion, there was a variation of obesity prevalence of the provinces within and between island clusters. The variation of risk factors found in each island cluster suggests that a government rethink of the current intervention strategies to address obesity is recommended.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 88%

Obesity Risk-Factor Variation Based on Island Clusters: A Secondary Analysis of Indonesian Basic Health Research 2018

et al. 2022

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“…Furthermore, we also noted that physical activity was a predictor of obesity in all island clusters. This result was consistent with many studies conducted in Indonesia and elsewhere that reported that physical activity is strongly associated with obesity [30][31][32][33][34][35]. Performing sufficient physical activity might be beneficial to maintain people's energy expenditure and subsequent energy balance.…”

Section: Discussionsupporting

confidence: 91%

“…Jakarta is the biggest metropolitan city in Indonesia where the population has a higher odd of following sedentary behavior and consuming more "unhealthy foods" than other small cities. A similar finding was reported by a study in Ethiopia that found that men living in metropolitan cities 1.8 times were more likely to become obese than those living in rural areas [32].…”

Section: Discussionsupporting

confidence: 88%

Obesity Risk Factor Variation Based on Islands Cluster: A Secondary Analysis of Indonesian Basic Health Research 2018

Thamrin¹,

Arsyad²,

Kuswanto³

et al. 2022

Preprint

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Obesity has become a rising global health problem affecting adults’ quality of life. The objective of this study was to describe the prevalence of obesity in Indonesian adults based on the cluster of islands. The study was also aimed to identify the risk factors of obesity in each island cluster. This study analysed secondary data of Indonesian Basic Health Research 2018. Our data for analysis comprised 688,638 adults (>=15 years) randomly selected using proportionate to population size throughout Indonesia. We included 20 variables for sociodemographic and obesity-related risk factors for analysis. Obese status was defined using Body Mass Index (BMI) >= 27.5 kg/m2. Our current study defined seven major islands cluster as the unit analysis consisting of 34 provinces in Indonesia. Descriptive analysis was conducted to determine the characteristics of the population and to calculate the prevalence of obesity within provinces in each of the island’s clusters. Multivariate logistic regression analyses to calculate odds ratios (ORs) was performed using R version 3.6.3. The study results showed that all island clusters had at least one province with an obesity prevalence of more than 20%. Six out of twenty variables, comprising four diet factors (consumption of sweet food, high-salt food, meat food, and carbonated drinks) and two other factors (mental health disorders and smoking behaviour), varied across the island clusters. In conclusion, there was a variation of obesity prevalence of the provinces within and between island clusters. Variation of risk factors raised in each cluster island suggested the government rethink and reframe the intervention to address obesity.

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“…This might be explained by the hypothesis that employed adults might have better access to foods than their counterparts. Previous studies in Ethiopia suggested that unemployed men are less likely to be obese compared to employed men (52). This finding contradicts a study conducted in North Glasgow, UK, which reported that unemployed men and women were less likely to be centrally obese compared to full-time workers (53).…”

Section: Discussionmentioning

confidence: 95%

Prevalence of central obesity and its associated risk factors among adults in Southeast Ethiopia: a community-based cross-sectional study

Tekalegn

Solomon

Sahiledengle

et al. 2022

Preprint

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Background Obesity and overweight are known are public health scourge challenges affecting populations across the world. These conditions have been associated with a wide range of chronic diseases including type 2 diabetes mellitus, cardiovascular disease, and cancers. In Ethiopia, literature regarding the burden of central (abdominal) obesity is scarce. This study aimed to fill this gap by assessing the prevalence and risk factors associated with central obesity among adults in Ethiopia. Methods From May to July 2021, a community-based cross-sectional survey was conducted on a sample of 694 adults aged >=18 years in administrative towns of Bale zone, Southeast Ethiopia. Multi-stage sampling followed by systematic random sampling was employed to identify study participants. Waist and hip circumferences were measured using standard protocols. The World Health Organization STEPS wise tool was used to assess risk factors associated with central obesity. Bi-variable and multi-variable binary logistic regression were used to identify factors associated with central obesity. Adjusted odds ratios (AOR) and their corresponding 95% confidence intervals (CI) were reported to estimate the strength of associations. Results The overall prevalence of central obesity using waist circumference was 39.01% (15.44% for men and 53.12% for women). Multi-variable binary logistic regression analysis revealed that female sex (AOR=12.93, 95% CI: 6.74-24.79), Age groups: 30-39 years old (AOR=2.8, 95% CI: 1.59-4.94), 40-49 years (AOR=7.66, 95% CI: 3.87-15.15), 50-59 years (AOR=4.65, 95% CI: 2.19-9.89), >=60 years (AOR=12.67, 95% CI: 5.46-29.39), occupational status like: housewives (AOR=5.21, 95% CI: 1.85-14.62), self-employed workers (AOR=4.63, 95% CI: 1.62-13.24), government/private/non-government employees (AOR=4.68, 95% CI: 1.47-14.88) and skipping breakfast (AOR=0.46, 95% CI: 0.23-0.9) were significantly associated with central obesity. Conclusions Abdominal obesity has become an epidemic in towns of southeast Ethiopia, and the prevalence is higher among women. Female sex, older age group, being employed, not skipping breakfast were significantly associated with central obesity.

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Individual and community-level determinants of overweight and obesity among urban men: Further analysis of the Ethiopian demographic and health survey

Cited by 8 publications

References 47 publications

Obesity Risk-Factor Variation Based on Island Clusters: A Secondary Analysis of Indonesian Basic Health Research 2018

Obesity Risk-Factor Variation Based on Island Clusters: A Secondary Analysis of Indonesian Basic Health Research 2018

Obesity Risk Factor Variation Based on Islands Cluster: A Secondary Analysis of Indonesian Basic Health Research 2018

Prevalence of central obesity and its associated risk factors among adults in Southeast Ethiopia: a community-based cross-sectional study

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