Dual burden of underweight and overweight/obesity among adults in Botswana: prevalence, trends and sociodemographic correlates: a cross-sectional survey

Chronic Illness, Nutritional Status, and Factors Associated with Malnutrition among Various Age Groups Residing in Urban Areas of Telangana and Rural Areas of Andhra Pradesh

Malnutrition includes both under-nutrition and over-nutrition, which have negative health impacts and social consequences. The present study aims to understand the demographic dynamics, burden of chronic illnesses, and risk factors associated with malnutrition (stunting, thinness, and obesity) among different age groups in urban and rural areas. Data were collected through a cross-sectional study conducted in an urban area in Hyderabad and four rural villages in Andhra Pradesh. A multivariable mixed-effect logistic regression was used to assess the risk factors associated with malnutrition among different age groups. The final analysis included the data of 10,350 individuals, consisting of 8317 (80.4%) from urban areas and 2033 (19.6%) from rural areas. The number of known cases of hypertension in the urban area was 926 (11.1%) and 114 (5.6%) in the rural areas, and that of diabetes was 511 (6.1%) in the urban area and 104 (5.1%) in the rural areas. The burden of stunting among under-five children and obesity among adults was 33.7% (95% CI; 29.7-37.9) and 47.4% (95% CI; 45.8-49.1), respectively. Adults aged 40-59 years (AOR 1.91; 1.59-2.28) and belonging to a clerical/skilled (AOR 1.32; 1.03-1.71) occupation were at higher odds of obesity compared to their counterparts. Policymakers and health practitioners should consider the insights from our findings to tailor effective interventions to address malnutrition.

Spatial variation of overweight/obesity and associated factor among reproductive age group women in Ethiopia, evidence from EDHS 2016

BACKGROUND

Globally, at least 4.7 million people die from being overweight or obese. In Ethiopia, the level of overweight and obesity among women grew from 3% to 8%. However, as far as my literature searching, studies concerning the spatial variation of overweight/obesity and factors associated are not researched in Ethiopia using geospatial techniques. Therefore, this study aimed to explore the spatial variation of overweight/obesity and factor associated among reproductive age group women in Ethiopia using geospatial techniques.

MOTHED

A total weighted sample of 10,928 reproductive age women were included in the study. ArcGIS version10.7 was used to explore the spatial variation of overweight/obesity. Bernoulli based model was used to analyze the purely spatial cluster detection of overweight/obesity through SaTScan version 9.6.1 software. Ordinary Least Square analysis and geographically weighted regression analysis was employed to assess the association between an outcome variable and explanatory variables by using ArcGIS 10.7 software. P value of less than 0.05 was used to declare statically significant.

RESULT

The spatial distribution of overweight/obesity in Ethiopia was clustered. Statistically, a significant-high hot spot overweight/obesity was identified at Addis Ababa, harrari, Dire Dawa. SaTScan identified 66 primary spatial clusters (RR = 4.17, P < 0.001) located at Addis Ababa, southeast amhara, central part of oromia region and northern part of SNNP region. In geographically weighted regression, rich wealth index, women's age (35-39 and 40-44 years), watching TV, internet use and not working were statistically significant that affecting spatial variation of overweight/obesity.

CONCLUSION

In Ethiopia, overweight/obesity varies across the region. Statistically, significant-high hot spots of overweight/obesity were detected in Addis Ababa, Harari, Dire Dawa, some parts of Amhara and afar region, most of the Oromia and Somalia region, and the South Nation Nationality and People region of Ethiopia. Therefore, the ministry of health and the Ethiopian public health institute, try to initiate policies and practices that could include providing funding for physical education as well as recreational centers in communities most in need. In addition, public and private mass media create awareness of healthy lifestyles is promoted by health education regarding increased physical activity and reduced sedentary behavior through various media platforms.

Prevalence and Socio-Demographic Correlates of Body Weight Categories Among South African Women of Reproductive Age: A Cross-Sectional Study

Background: The shift in disease patterns has been connected with increased body weight burden, becoming a major public health concern in South Africa, as previous studies have assessed overweight or obesity among certain populations. However, little is known about bodyweight burden (underweight, overweight, and obesity) among women aged 15-49 years. Therefore, this study was conducted to identify the prevalence and its associated socio-demographic correlates of bodyweight categories among women of reproductive age in South Africa. Methods: The present study used the South Africa Demographic Health Survey (2016 SADHS) data for 2016. A total of 3,263 women of reproductive age were included in the analysis. Both bivariable and multivariable logistics regressions were performed to determine the prevalence and socio-demographic correlates of bodyweight categories among women in South Africa. Thus, this study used the criteria of the WHO standard body mass index (BMI) cut-offs to classify bodyweight categories. The odds ratios (ORs) with 95% CIs were estimated for potential determinants included in the final model. Results: The overall prevalence of body weight burden was 66.5%, with 4.9% underweight, 27.1% overweight, and 34.5% obese (p < 0.05). The identified factors associated with underweight among women of reproductive age were those from "other" population group [adjusted odds ratio (AOR) 2.65: 95% CI 1.40-5.00], rural residence (AOR 1.23: 95% CI 0.75-2.02), and Northern Cape Province (AOR 1.58: 95% CI 0.65-3.87). For overweight/obese, the main factors were those aged 45-49 years (AOR 10.73: 95% CI 7.41-15.52), tertiary education (AOR 1.41: 95% CI 0.97-2.03), and residing in Eastern Cape (AOR 1.27: 95% CI 0.82-1.99) and KwaZulu-Natal Provinces (AOR 1.20: 95% CI 0.78-1.84). Conclusion: The findings presented in this study indicate the concurrence of underweight and overweight/obese among women aged 15-49 years in South Africa. Despite underweight prevalence being on the decline, yet overweight/obese is increasing over time. The health implication of body weight burden needs rapid and effective interventions, focusing on factors such as rural, education, population group, older age 45-49 years, and Provinces (Northern Cape, Eastern Cape, and KwaZulu-Natal) - the high-risk groups identified herein are of most importance to curb the growing burden among South African women of reproductive age.

Gender differences in dietary behaviours, health-related habits and prevalence of non-communicable diseases in Botswana

The aim of this study was to assess gender differences in the prevalence non-communicable diseases (NCDs) and in associated health-related habits, weight status and common risk factors in Botswana. Data were from the cross-sectional, population-based Botswana STEPS Survey II conducted in 2014. A total sample of 2947 survey participants aged 25–64 years were included the study. The results showed that a statistically significant higher percentage of men used tobacco compared with women (34.4%, 95% CI: 33.5–35.1 vs 4.4%, 95% CI: 4.3–4.5). Men also had consistently and statistically significantly greater heavy alcohol consumption and lower fruit and/or vegetable consumption than women. Physical inactivity among women was higher than in men. Controlling for other factors, men had a higher probability of being overweight (28.7%, 95% CI: 28.6–28.8 vs 18.3%, 95% CI: 18.0–18.6) and obese (25.8%, 95% CI: 25.4–26.2 vs 10.2%, 95% CI: 9.9–10.5) than women. Women were at a greater risk of developing NCDs compared with men since their adjusted prevalence of having at least three common risk factors was higher than men’s. Women had a higher adjusted predicted prevalence of suffering from hypertension than men (39.4%, 95% CI: 38.9–40.0 vs 26.1%, 95% CI: 25.5–26.8). Appropriate policies and programmes need to be adopted to urgently address the problem of NCDs in Botswana.

Prevalence and correlates of multimorbidity among adults in Botswana: A cross-sectional study

BACKGROUND

Botswana is currently undergoing rapid epidemiological transition indicated by a decline in infectious diseases and an increase in chronic non-communicable diseases and their associated risk factors. The main aim of this study was to assess prevalence and correlates of multimorbidity among the adult population in Botswana.

METHODS

A cross-sectional study called Chronic Non-Communicable Diseases Study (NCDs study) was conducted in March, 2016. Using multistage cross sectional sampling design, 1178 male and female respondents aged 15 years and above were interviewed across 3 cities and towns, 15 urban villages and 15 rural villages. Participants were interviewed face-to-face using a structured questionnaire. Adjusted multinomial logistic regression analysis was used to assess covariates of multimorbidity. The statistical significant level was fixed at p <0 .05.

RESULTS

Prevalence of multimorbidity in the sampled population was estimated at 5.4%. Multivariate results indicate that the odds of multimobridty were significantly high among women (AOR = 3.34, 95% C.I. = 1.22-21.3) than men. On the other hand, the odds of multimorbidity were significantly low among young people aged below 24 years (AOR = 0.01, 95% C.I. = 0.00-0.07), currently married people (AOR = 0.24, 95% C.I. = 0.07-0.80) and individuals in the 2nd wealth quintile (AOR = 0.20, 95% C.I. = 0.05-0.75) compared to their counterparts. For behavioural risk factors, alcohol consumption (AOR = 4.80, 95% C.I. = 1.16-19.8) and overweight/obesity (AOR = 1.44, 95% CI = 1.12-2.61) were significantly associated with high multimorbidity prevalence.

CONCLUSION

Multimorbidity was found to be more prevalent among women, alcohol consumers and overweight/obese people. There is need to strengthen interventions encouraging healthy lifestyles such as non-consumption of alcohol, physical activity and healthy diets. Moreover, there is need for a holistic approach of health care services to meet the needs of those suffering from multimorbidity.