Dataset Information

Body mass index and wealth index: positively correlated indicators of health and wealth inequalities in Nairobi slums.

ABSTRACT:

Introduction

Wealth index is a known predictor of body mass index (BMI). Many studies have reported a positive association between BMI and socioeconomic status (SES). However, an in-depth investigation of the relationship between BMI and wealth index is lacking for urban slum settings.

Objective

To examine the association between BMI and wealth index in an urban slum setting in Nairobi, Kenya.

Methods

A total of 2003 adults between 40 and 60 years of age were included. BMI was derived from direct weight and height measurements. Wealth Index was computed using the standard principal component analysis of household amenities ownership. The relationship between BMI and wealth index was assessed using both linear and logistic regression models.

Results

We found that BMI linearly increased across the five quintiles of wealth index in both men and women, after adjusting for potential confounding factors. The prevalence of obesity increased from 10% in the first wealth quintile to 26.2% in the fifth wealth quintile. The average BMI for women entered the overweight category at the second quintile wealth status, or the third quintile for the total population.

Conclusion

There exists a strong positive relationship between BMI and wealth index in slum settings. Health promotion interventions aimed at reducing obesity may consider using wealth index in priority setting.

SUBMITTER: Haregu TN

PROVIDER: S-EPMC6152486 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Body mass index and wealth index: positively correlated indicators of health and wealth inequalities in Nairobi slums.

Haregu T N TN Mohamed S F SF Muthuri S S Khayeka-Wandabwa C C Kyobutungi C C

Global health, epidemiology and genomics 20180604

<h4>Introduction</h4>Wealth index is a known predictor of body mass index (BMI). Many studies have reported a positive association between BMI and <i>socioeconomic status</i> (SES). However, an in-depth investigation of the relationship between BMI and wealth index is lacking for urban slum settings.<h4>Objective</h4>To examine the association between BMI and wealth index in an urban <i>slum</i> setting in Nairobi, Kenya.<h4>Methods</h4>A total of 2003 adults between 40 and 60 years of age were ...[more]

PMID: 30263135

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Project description:BACKGROUND:In contrast with the ample literature on within- and between-country inequalities in breastfeeding practices, there are no multi-country analyses of socioeconomic disparities in breastmilk substitute (BMS) consumption in low- and middle-income countries (LMICs). OBJECTIVE:This study aimed to investigate between- and within-country socioeconomic inequalities in breastfeeding and BMS consumption in LMICs. METHODS:We examined data from the Demographic Health Surveys and Multiple Indicator Cluster Surveys conducted in 90 LMICs since 2010 to calculate Pearson correlation coefficients between infant feeding indicators and per capita gross domestic product (GDP). Within-country inequalities in exclusive breastfeeding, intake of formula or other types of nonhuman milk (cow/goat) were studied for infants aged 0-5 mo, and for continued breastfeeding at ages 12-15 mo through graphical presentation of coverage wealth quintiles. RESULTS:Between-country analyses showed that log GDP was inversely correlated with exclusive (r = -0.37, P < 0.001) and continued breastfeeding (r = -0.74, P < 0.0001), and was positively correlated with formula intake (r = 0.70, P < 0.0001). Continued breastfeeding was inversely correlated with formula (r = -0.79, P < 0.0001), and was less strongly correlated with the intake of other types of nonhuman milk (r = -0.40, P < 0.001). Within-country analyses showed that 69 out of 89 did not have significant disparities in exclusive breastfeeding. Continued breastfeeding was significantly higher in children belonging to the poorest 20% of households compared with the wealthiest 20% in 40 countries (by ?30 percentage points on average), whereas formula feeding was more common in the wealthiest group in 59 countries. CONCLUSIONS:BMS intake is positively associated with GDP and negatively associated with continued breastfeeding in LMICs. In most countries, BMS intake is positively associated with family wealth, and will likely become more widespread as countries develop. Urgent action is needed to protect, promote, and support breastfeeding in all income groups and to reduce the intake of BMS, in light of the hazards associated with their use.

Project description:ImportanceBody mass index (BMI) is used to diagnose obesity in adolescents worldwide, despite evidence that weight does not scale with height squared in adolescents. To account for this, health care providers diagnose obesity using BMI percentiles for each age (BMI z scores), but this does not ensure that BMI is accurate in adolescents.ObjectiveTo compare the accuracy of BMI vs other body fat indices of the form body mass divided by heightn in estimating body fat levels in adolescents.Design, setting, and participantsCross-sectional data from the 1999 to 2006 US National Health and Nutrition Examination Survey were analyzed between September 2015 and December 2016.Main outcomes and measuresDual-energy x-ray absorptiometry and anthropometric data were used to determine changes in body fat levels, body proportions, and the scaling relationships among body mass, height, and percent body fat. To assess the merits of each adiposity index, 3 criteria were used: stability with age, accuracy in estimating percent body fat, and accuracy in classifying adolescents as overweight vs normal weight.ResultsParticipants included 2285 non-Hispanic white participants aged 8 to 29 years. Percent body fat varied with both age and height during adolescence, invalidating the standard weight-to-height regression as the way of finding the optimal body fat index. Because the correct regression model (percent body fat is proportional to mass divided by heightn) suggested that percent body fat scales to height with an exponent closer to 3, we therefore focused on the tri-ponderal mass index (TMI; mass divided by height cubed) as an alternative to BMI z scores. For ages 8 to 17 years, TMI yielded greater stability with age and estimated percent body fat better than BMI (R2?=?0.64 vs 0.38 in boys and R2?=?0.72 vs 0.66 in girls). Moreover, TMI misclassified adolescents as overweight vs normal weight less often than BMI z scores (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 19.4%; 95% CI, 17.8%-20.0%; P?<?.001) and performed equally as well as updated BMI percentiles derived from the same data set (TMI, 8.4%; 95% CI, 7.3%-9.5% vs BMI, 8.0%; 95% CI, 6.9%-9.1%; P?=?.62).Conclusions and relevanceThe tri-ponderal mass index estimates body fat levels more accurately than BMI in non-Hispanic white adolescents aged 8 to 17 years. Moreover, TMI diagnoses adolescents as overweight more accurately than BMI z scores and equally as well as updated BMI percentiles but is much simpler to use than either because it does not involve complicated percentiles. Taken together, it is worth considering replacing BMI z scores with TMI to estimate body fat levels in adolescents.

Dataset Information

Body mass index and wealth index: positively correlated indicators of health and wealth inequalities in Nairobi slums.

Introduction

Objective

Methods

Results

Conclusion

Publications

Body mass index and wealth index: positively correlated indicators of health and wealth inequalities in Nairobi slums.

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