Using quadratic inference functions to determine the factors associated with obesity: findings from the STEPS Survey in Iran

Prevalence of overweight and obesity among Iranian population: a systematic review and meta-analysis

BACKGROUND

Obesity is a major risk factor for chronic diseases. Politicians and practitioners should be aware of the dramatic increase in obesity and its subsequent complications to prevent associated health risks. This systematic review aimed to provide better insight into the prevalence of overweight and obesity in the Iranian population.

METHOD

An evaluation was conducted on all published observational studies from both national (SID, Irandoc, Iranmedex) and international (Web of Knowledge, PubMed, Scopus) sources, which reported the prevalence of overweight/obesity among normal population samples, between January 2012 and December 2021.

RESULT

A total of 152 eligible studies were included in this meta-analysis. Of the 152 selected studies, 74 reported the prevalence of overweight/obesity in patients aged ≤ 18 years, and 61 studies in adults. In the rest of the articles (17 studies), the results were reported for a combination of these age groups. The prevalence of overweight and obesity in Iran was estimated at 20.1 (95% CI 17.92-22.30) and 13.44 (95% CI 11.76-15.22), respectively. This percentage (95% CI) was 11.71 (10.98-12.46) for overweight and 8.08 (7.02-9.22) for obesity in those aged ≤ 18 years, and 35.26 (32.61-37.99) for overweight and 21.38 (19.61-23.20) for obesity in those aged > 18 years. The overall prevalence of overweight and obesity in the entire population was 35.09% (95% CI 31.31-38.98).

CONCLUSION

As obesity is on the rise in Iran, we should seek both weight loss strategies and ways to control comorbidities associated with high BMI.

An evaluation of quadratic inference functions for estimating intervention effects in cluster randomized trials

Cluster randomized trials (CRTs) usually randomize groups of individuals to interventions, and outcomes are typically measured at the individual level. Marginal intervention effects are frequently of interest in CRTs due to their population-averaged interpretations. Such effects are estimated using generalized estimating equations (GEE), or a recent alternative called the quadratic inference function (QIF). However, the performance of QIF relative to GEE have not been extensively evaluated in the CRT context, especially when the marginal mean model includes additional covariates. Motivated by the HALI trial, we conduct simulation studies to compare the finite-sample operating characteristics of QIF and GEE. We demonstrate that QIF and GEE are equivalent under some conditions. When the marginal mean model includes individual-level covariates, QIF shows an efficiency improvement over GEE with overall larger power, but its test size may be more liberal than GEE and GEE achieves better coverage than QIF. The test size inflation may not by fully addressed from using finite-sample bias corrections. The estimates of QIF tend to be closer to GEE in the HALI data, although the former presents a small standard error. Overall, we confirm that the QIF approach generally has potentially better efficiency than GEE in our simulation studies but might be more cautiously used as a viable approach for the analysis of CRTs. More research is needed, however, to address the finite-sample bias in the variance estimation of the QIF to better control its test size.

Application of the Marginal Beta-Binomial Model in Estimation the Overall Odds of Obesity Among Iranian Adults: Meta-Analysis Method

CONTEXT

To obtain accurate and reliable estimation of overall obesity odds ratio (OR) a statistical method is needed to be designed to account for heterogeneity among studies. The marginal beta-binomial model is a new method with attractive features that make it robust for meta-analysis.

OBJECTIVES

The aim of this study is the estimation of overall obesity OR among Iranian adults with particularly attention to age, sex, place of residence, and smoking status.

DATA SOURCES

We systematically reviewed all studies regarding obesity in Iranian adults in national and international journals that are published between 1990 and 2017, including PubMed, Scopus, SID, Google Scholar, Magiran, and IranMedex. The R software was used for data analysis and obtaining overall obesity OR using the marginal beta-binomial model.

RESULTS

A total of 18 studies, with a sample size of 258283, were included in our analysis. Results showed that increasing age, female sex, and residence in urban areas increases the odds of obesity. Using the age group 20 - 30 years as the reference, the overall obesity ORs for 30 - 40, 40 - 50, 50 - 60, and 60+ years were 2.13, 3.33, 3.15, and 2.33, respectively. The overall obesity OR for women was 2.35, compared with men. The estimated odds of obesity were 53% higher for urban adults. Smoking has a negative effect on obesity; the OR of obesity for smokers was 0.48 compared with non-smokers.

CONCLUSION

Consistent results in our research can be used as a basis to reinforce health programs for prevention and treatment of obesity in Iran.

Obesity and its socioeconomic determinants in Iran

OBJECTIVE

To investigate the socioeconomic inequality of obesity and its determinants in Iran.

METHODS

Data was from Iran's surveillance system for risk factors of non-communicable diseases which was conducted on 89,400 individuals aged 15-64 years in 2005. Principal component analysis was used to create a new variable for defining socioeconomic status of participants. We assessed inequality by calculating a slop index of inequality and concentration index for obesity. Oaxaca-Blinder decomposition analysis was used to determine the determinants of inequality.

RESULTS

The slop index of inequality and concentration index for obesity was -13.1 (95% Confidence Intervals [CI]: -16.3 to -9.8) percentage points and -0.123, respectively. The level of inequality varied widely between different provinces in Iran and was more severe in women and urban population. Obesity persisted in 20.2% (95% CI: 19.4-20.9) of the low-socioeconomic group and 11.0% (95% CI: 10.5-11.6) of the high-socioeconomic group. More than 90% of this gap was due to differences of independent variables (mainly age, gender and marital status) in two socioeconomic status groups.

CONCLUSIONS

A pro-rich inequality existed in the obesity in Iran. Older age, female gender and rural residency contributed most to the economic inequality of obesity.

Review of Recent Methodological Developments in Group-Randomized Trials: Part 2-Analysis

In 2004, Murray et al. reviewed methodological developments in the design and analysis of group-randomized trials (GRTs). We have updated that review with developments in analysis of the past 13 years, with a companion article to focus on developments in design. We discuss developments in the topics of the earlier review (e.g., methods for parallel-arm GRTs, individually randomized group-treatment trials, and missing data) and in new topics, including methods to account for multiple-level clustering and alternative estimation methods (e.g., augmented generalized estimating equations, targeted maximum likelihood, and quadratic inference functions). In addition, we describe developments in analysis of alternative group designs (including stepped-wedge GRTs, network-randomized trials, and pseudocluster randomized trials), which require clustering to be accounted for in their design and analysis.

Changes in Obesity Odds Ratio among Iranian Adults, since 2000: Quadratic Inference Functions Method

Background. Monitoring changes in obesity prevalence by risk factors is relevant to public health programs that focus on reducing or preventing obesity. The purpose of this paper was to study trends in obesity odds ratios (ORs) for individuals aged 20 years and older in Iran by using a new statistical methodology. Methods. Data collected by the National Surveys in Iran, from 2000 through 2011. Since responses of the member of each cluster are correlated, the quadratic inference functions (QIF) method was used to model the relationship between the odds of obesity and risk factors. Results. During the study period, the prevalence rate of obesity increased from 12% to 22%. By using QIF method and a model selection criterion for performing stepwise regression analysis, we found that while obesity prevalence generally increased in both sexes, all ages, all employment, residence, and smoking levels, it seems to have changes in obesity ORs since 2000. Conclusions. Because obesity is one of the main risk factors for many diseases, awareness of the differences by factors allows development of targets for prevention and early intervention.

An association of platelet indices with blood pressure in Beijing adults: Applying quadratic inference function for a longitudinal study

The quadratic inference function (QIF) method becomes more acceptable for correlated data because of its advantages over generalized estimating equations (GEE). This study aimed to evaluate the relationship between platelet indices and blood pressure using QIF method, which has not been studied extensively in real data settings.A population-based longitudinal study was conducted in Beijing from 2007 to 2012, and the median of follow-up was 6 years. A total of 6515 cases, who were aged between 20 and 65 years at baseline and underwent routine physical examinations every year from 3 Beijing hospitals were enrolled to explore the association between platelet indices and blood pressure by QIF method. The original continuous platelet indices were categorized into 4 levels (Q1-Q4) using the 3 quartiles of P25, P50, and P75 as a critical value. GEE was performed to make a comparison with QIF.After adjusting for age, usage of drugs, and other confounding factors, mean platelet volume was negatively associated with diastolic blood pressure (DBP) (Equation is included in full-text article.)in males and positively linked with systolic blood pressure (SBP) (Equation is included in full-text article.). Platelet distribution width was negatively associated with SBP (Equation is included in full-text article.). Blood platelet count was associated with DBP (Equation is included in full-text article.)in males.Adults in Beijing with prolonged exposure to extreme value of platelet indices have elevated risk for future hypertension and evidence suggesting using some platelet indices for early diagnosis of high blood pressure was provided.

A comparison of food pattern, macro- and some micronutrients density of the diet across different socio-economic zones of Tehran

Background: The consumption of low quality foods is common in low socioeconomic areas; and according to epidemiological studies, the density of nutrients often proves the quality of diet. This study aimed to compare the density of macronutrients and micronutrients in various parts of Tehran.

Methods: This was a cross-sectional study performed from September to December 2007 in all the 22 districts of the municipality of Tehran including 1,807 households. Experienced interviewers completed a 24-hour recall questionnaire. To estimate the nutrient densities, nutrient intake (grams or milligrams) was calculated per 1,000 kcal energy intake. To calculate the density of energy intake, energy intake (kcal) was divided by 100 g of foodstuff. The 22 districts of Tehran were divided into five zones of north, center, east, west and south. ANOVA and Tukey tests were used.

Results: The highest density of protein and fat intake was observed in the north of Tehran, while carbohydrate density was highest in the west, east and south zones, and energy density was highest in the south zone (p<0.05). Calcium and vitamin C had the highest density in the north of Tehran, and vitamin A and riboflavin had the highest density in the north and center of Tehran, and the lowest level in the south of Tehran (p<0.05).

Conclusion: Despite the high density of energy in the south of Tehran, a deficiency of micronutrient intake was obvious, reflecting the importance of the impact of socioeconomic factors.

Assessing factors related to waist circumference and obesity: application of a latent variable model

Background. Because the use of BMI (Body Mass Index) alone as a measure of adiposity has been criticized, in the present study our aim was to fit a latent variable model to simultaneously examine the factors that affect waist circumference (continuous outcome) and obesity (binary outcome) among Iranian adults. Methods. Data included 18,990 Iranian individuals aged 20–65 years that are derived from the third National Survey of Noncommunicable Diseases Risk Factors in Iran. Using latent variable model, we estimated the relation of two correlated responses (waist circumference and obesity) with independent variables including age, gender, PR (Place of Residence), PA (physical activity), smoking status, SBP (Systolic Blood Pressure), DBP (Diastolic Blood Pressure), CHOL (cholesterol), FBG (Fasting Blood Glucose), diabetes, and FHD (family history of diabetes). Results. All variables were related to both obesity and waist circumference (WC). Older age, female sex, being an urban resident, physical inactivity, nonsmoking, hypertension, hypercholesterolemia, hyperglycemia, diabetes, and having family history of diabetes were significant risk factors that increased WC and obesity. Conclusions. Findings from this study of Iranian adult settings offer more insights into factors associated with high WC and high prevalence of obesity in this population.

Obesity and Related Factors in Iran: The STEPS Survey, 2011

Background:

To date, no study has addressed the association between race/ethnicity and obesity considering other sociodemographic and lifestyle factors in Iran.

Objectives:

The current study aimed to study lifestyle and the environmental factors affecting obesity in the Iranian subjects of the STEPS Survey, 2011.

Patients and Methods:

The study was conducted on 8639 subjects (aged ≥ 20 years) in the STEPS Survey 2011 in Iran under supervision of the World Health Organization (WHO). Height and body weight were measured following the standardized procedures. Generalized Estimating Equations (GEE) method was used to examine factors associated with obesity. The examined variables were age, gender, race/ethnicity, place of residence, employment status, physical activity, smoking status, and educational level.

Results:

Overall, 22.3% of the subjects were obese. In a GEE model, a healthy weight status among adults was associated with being younger, male, in a rural residence, employees, spending more time engaged in physical activity, being a smoker and having a moderate or high level of education. These associations were statistically significant after adjusting for other variables.

Conclusions:

The study results suggest a need for targeted interventions and continued surveillance for the Iranian adults.