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      Prevalence and Predictors of Overweight and Obesity Among Kenyan Women

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      Author(s): , MPH, CPH 1 , , MPH 2 , , MPH, MPS, MSc 3 ,
      Publication date (Electronic):
      Journal: Preventing Chronic Disease
      Publisher: Centers for Disease Control and Prevention

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          Abstract

          Introduction

          Overweight and obesity are associated with increased rates of chronic disease and death globally. In Kenya, the prevalence of overweight and obesity among women is high and may be growing. This study aimed to determine the national prevalence and predictors of overweight and obesity among women in Kenya.

          Methods

          We used cross-sectional data from the 2014 Kenya Demographic and Health Survey (KDHS). Data on body mass index for 13,048 women (aged 15–49 y) were analyzed by using multivariable logistic regression models. Overweight and obesity were classified by using World Health Organization categories (normal weight, 18.5 to <24.9; overweight, 25.0 to <29.9; and obese, ≥30.0).

          Results

          The prevalence of overweight was 20.5%, and the prevalence of obesity, 9.1%. Women aged 35 to 44 (odds ratio [OR] = 3.14; 95% confidence interval [CI], 2.58−3.81), with more than a secondary education (OR = 1.43; 95% CI, 1.05–1.95), married or living with a partner (OR = 1.73; 95% CI, 1.42−2.08), not working (OR = 1.27; 95% CI, 1.10–1.48), in the richest category (OR = 6.50; 95% CI, 5.08–8.30), and who used hormonal contraception (OR = 1.24; 95% CI, 1.07–1.43) were significantly more likely to be overweight or obese.

          Conclusion

          A high proportion of women in Kenya are overweight or obese. Our study indicates that women from urban areas and women with high socioeconomic status make up the largest proportion of women who are overweight or obese. Targeted and tailored studies and interventions are needed to identify evidence-based obesity prevention strategies for high-risk women in Kenya.

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          Constructing socio-economic status indices: how to use principal components analysis.

          S Vyas, L Kumaranayake (2006)
          Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCA-based indices are constructed, how they can be used, and their validity and limitations. Specifically, issues related to choice of variables, data preparation and problems such as data clustering are addressed. Interpretation of results and methods of classifying households into SES groups are also discussed. PCA has been validated as a method to describe SES differentiation within a population. Issues related to the underlying data will affect PCA and this should be considered when generating and interpreting results.
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            National, regional, and global levels and trends in maternal mortality between 1990 and 2015 with scenario-based projections to 2030: a systematic analysis by the United Nations Maternal Mortality Estimation Inter-Agency Group

            Leontine Alkema, Doris Chou, Daniel W Hogan … (2015)
            Summary Background Millennium Development Goal (MDG) 5 calls for a reduction of 75% in the maternal mortality ratio (MMR) between 1990 and 2015. We estimated levels and trends in maternal mortality for 183 countries to assess progress made. Based on MMR estimates for 2015, we constructed scenario-based projections to highlight the accelerations needed to accomplish the Sustainable Development Goal (SDG) global target of less than 70 maternal deaths per 100,000 live births globally by 2030. Methods We updated the open access UN Maternal Mortality Estimation Inter-agency Group (MMEIG) database. Based upon nationally-representative data for 171 countries, we generated estimates of maternal mortality and related indicators with uncertainty intervals using a Bayesian model, which extends and refines the previous UN MMEIG estimation approach. The model combines the rate of change implied by a multilevel regression model with a time series model to capture data-driven changes in country-specific MMRs, and includes a data model to adjust for systematic and random errors associated with different data sources. Results The global MMR declined from 385 deaths per 100,000 live births (80% uncertainty interval ranges from 359 to 427) in 1990 to 216 (207 to 249) in 2015, corresponding to a relative decline of 43.9% (34.0 to 48.7) during the 25-year period, with 303,000 (291,000 to 349,000) maternal deaths globally in 2015. Regional progress in reducing the MMR since 1990 ranged from an annual rate of reduction of 1.8% (0 to 3.1) in the Caribbean to 5.0% (4.0 to 6.0) for Eastern Asia. Regional MMRs for 2015 range from 12 (11 to 14) for developed regions to 546 (511 to 652) for sub-Saharan Africa. Accelerated progress will be needed to achieve the SDG goal; countries will need to reduce their MMRs at an annual rate of reduction of at least 7.5%. Interpretation Despite global progress in reducing maternal mortality, immediate action is required to begin making progress towards the ambitious SDG 2030 target, and ultimately eliminating preventable maternal mortality. While the rates of reduction that are required to achieve country-specific SDG targets are ambitious for the great majority of high mortality countries, the experience and rates of change between 2000 and 2010 in selected countries–those with concerted efforts to reduce the MMR- provide inspiration as well as guidance on how to accomplish the acceleration necessary to substantially reduce preventable maternal deaths. Funding Funding from grant R-155-000-146-112 from the National University of Singapore supported the research by LA and SZ. AG is the recipient of a National Institute of Child Health and Human Development, grant # T32-HD007275. Funding also provided by USAID and HRP (the UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction).
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              Metabolic syndrome in childhood: association with birth weight, maternal obesity, and gestational diabetes mellitus.

              C. Boney (2005)
              Childhood obesity has contributed to an increased incidence of type 2 diabetes mellitus and metabolic syndrome (MS) among children. Intrauterine exposure to diabetes and size at birth are risk factors for type 2 diabetes mellitus, but their association with MS in childhood has not been demonstrated. We examined the development of MS among large-for-gestational-age (LGA) and appropriate-for-gestational age (AGA) children. The major components of MS (obesity, hypertension, dyslipidemia, and glucose intolerance) were evaluated in a longitudinal cohort study of children at age 6, 7, 9, and 11 years who were LGA (n = 84) or AGA (n = 95) offspring of mothers with or without gestational diabetes mellitus (GDM). The cohort consisted of 4 groups, ie, LGA offspring of control mothers, LGA offspring of mothers with GDM, AGA offspring of control mothers, and AGA offspring of mothers with GDM. Biometric and anthropometric measurements were obtained at 6, 7, 9, and 11 years. Biochemical testing included measurements of postprandial glucose and insulin levels and high-density lipoprotein (HDL) cholesterol levels at 6 and 7 years and of fasting glucose, insulin, triglyceride, and HDL cholesterol levels at 9 and 11 years. We defined the components of MS as (1) obesity (BMI >85th percentile for age), (2) diastolic or systolic blood pressure >95th percentile for age, (3) postprandial glucose level >140 mg/dL or fasting glucose level >110 mg/dL, (4) triglyceride level >95th percentile for age, and (5) HDL level 85th percentile) at 11 years was present in 25% to 35% of the children, but rates were not different between LGA and AGA offspring. There was a trend toward a higher incidence of insulin resistance, defined as a fasting glucose/insulin ratio of or =2 components of MS was 50% for the LGA/GDM group, which was significantly higher than values for the LGA/control group (29%), AGA/GDM group (21%), and AGA/control group (18%). The prevalence of > or =3 components of MS at age 11 was 15% for the LGA/GDM group, compared with 3.0% to 5.3% for the other groups. Cox regression analysis was performed to determine the independent hazard (risk) of developing MS attributable to birth weight, gender, maternal prepregnancy obesity, and GDM. For Cox analyses, we defined MS as > or =2 of the following 4 components: obesity, hypertension (systolic or diastolic), glucose intolerance, and dyslipidemia (elevated triglyceride levels or low HDL levels). LGA status and maternal obesity increased the risk of MS approximately twofold, with hazard ratios of 2.19 (95% CI: 1.25-3.82) and 1.81 (95% CI: 1.03-3.19), respectively. GDM and gender were not independently significant. To determine the cumulative hazard of developing MS with time, we plotted the risk according to LGA or AGA category for the control and GDM groups from 6 years to 11 years, with Cox regression analyses. The risk of developing MS with time was not significantly different between LGA and AGA offspring in the control group but was significantly different between LGA and AGA offspring in the GDM group, with a 3.6-fold greater risk among LGA children by 11 years. We showed that LGA offspring of diabetic mothers were at significant risk of developing MS in childhood. The prevalence of MS in the other groups was similar to the prevalence (4.8%) among white adolescents in the 1988-1994 National Health and Nutrition Examination Survey. This effect of LGA with maternal GDM on childhood MS was previously demonstrated for Pima Indian children but not the general population. We also found that children exposed to maternal obesity were at increased risk of developing MS, which suggests that obese mothers who do not fulfill the clinical criteria for GDM may still have metabolic factors that affect fetal growth and postnatal outcomes. Children who are LGA at birth and exposed to an intrauterine environment of either diabetes or maternal obesity are at increased risk of developing MS. Given the increased obesity prevalence, these findings have implications for perpetuating the cycle of obesity, insulin resistance, and their consequences in subsequent generations.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Prev Chronic Dis
                Journal ID (iso-abbrev): Prev Chronic Dis
                Journal ID (publisher-id): PCD
                Title: Preventing Chronic Disease
                Publisher: Centers for Disease Control and Prevention
                ISSN (Electronic): 1545-1151
                Publication date Collection: 2018
                Publication date (Electronic): 19 April 2018
                Volume: 15
                Electronic Location Identifier: E44
                Affiliations
                [1 ]Department of Health and Kinesiology, Texas A&M University, College Station, Texas
                [2 ]Statistics Collaborative, Inc, Washington, DC
                [3 ]Department of Emergency Medicine, University of Florida College of Medicine, Gainesville, Florida
                Author notes
                Corresponding Author: Muhammad Abdul Baker Chowdhury, MPH, MPS, MSc, Clinical Biostatistician, PO Box 100186, Gainesville, FL 32610-0186. Telephone: 352-265-5911 x31458. Email: mchow023@ 123456fiu.edu .
                Article
                Publisher ID: 17_0401
                DOI: 10.5888/pcd15.170401
                PMC ID: 5912924
                PubMed ID: 29679481
                SO-VID: bdc82789-0312-4bee-9337-53fca2ddd078
                History
                Categories
                Subject: Original Research
                Series title: Peer Reviewed

                ScienceOpen disciplines: Health & Social care
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                ScienceOpen disciplines: Health & Social care

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