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by Marie Joy F. Lopez Institute of Statistics, UPLB

ESTIMATING THE PREVALENCE OF YOUNG ADULT OBESITY IN PROVINCES AND HIGHLY URBANIZED CITIES IN THE PHILIPPINES USING POISSON REGRESSION WITH SPATIALLY AUTOCORRELATED RANDOM EFFECTS. by Marie Joy F. Lopez Institute of Statistics, UPLB. Prevalence of Malnutrition (1993-2013).

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by Marie Joy F. Lopez Institute of Statistics, UPLB

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  1. ESTIMATING THE PREVALENCE OF YOUNG ADULT OBESITY IN PROVINCES AND HIGHLY URBANIZED CITIES IN THE PHILIPPINES USING POISSON REGRESSION WITH SPATIALLY AUTOCORRELATED RANDOM EFFECTS by Marie Joy F. Lopez Institute of Statistics, UPLB

  2. Prevalence of Malnutrition (1993-2013) Children (0-5 years old) Adults (20 years old and above) 31.1% 16.6% Source: FNRI, 8TH NNS (2013)

  3. The “Double Burden Malnutrition” • Double Burden Malnutrition – a situation where overweight and obesity exist side by side with undernutrition • Possible Causes (Popkin, 2011): • Improvement of incomes • Increased industrialization • Urbanization and globalization • Diet of increasing energy density and higher level of sedentariness • Solution: Prevention Targeting High Risk Populations Identifying Obesogenic Environments

  4. Small Area Estimation - a statistical technique which involves estimation of parameters for small subpopulationor areas for which reliable statistics cannot be produced due to certain limitations of the available data. Regions Provinces Municipalities

  5. Methods • Indirect Estimation • an estimation procedure which utilize information from outside areas with similar characteristics to the area of interest. • estimates are obtained through a model which aims decrease the variability of the small area estimate • Poisson Model with Spatially Autocorrelated Random Effects • utilized to model count data which is usually the type of data of most health related outcomes • accounts for residual spatial dependence which may be present when the variable of interest is measured in areas that are geographically proximate. • “Accounting for spatial dependence tends to increase the percentage of variance explained for the dependent variable of a predictive model and does a surprisingly good job of compensating for unknown variables missing from a model. (Cressie, 1991)” • Defined as:

  6. Methods • Data Sources • Anthropometric Component of the 2008 NNS Survey • 2008 List of Establishment • 2007 Census of Population and Housing • Prevalence of Young Adult Obesity

  7. Results Correlates of the provincial level count of young adult obesity • Demographic Characteristics • Provincial count of household heads who have at least high school education (r=0.8005) • Provincial count of men with at least college education • (r=0.7625) • Economic Characteristics • Number of restaurants/cafes/ • fastfood in the city/province (r=0.7935) • Count of Financial Establishments • (r=0.7571) • Economic Characteristics • Provincial Count of Commercial Establishments • (r=0.7463)

  8. Results Spatial Autocorrelation Figure 1. Spatial correlogram of the total number of obese young adults.

  9. Results Spatial Autocorrelation Figure 2. Empirical semivariogram of the residuals from the Poisson model Figure 3. Empirical and fitted theoretical semivariogram of the residuals from the Poisson model

  10. Results Poisson Regression Model

  11. Results Distribution of the CVs

  12. NCR Results Distribution of the Estimates Figure 4. Distribution of the estimates of the prevalence of young adult obesity in the Philippines using the Poisson regression with spatially correlated random effects Figure 5. Choropleth map of the spatial Poisson estimates of the prevalence of young adult obesity in the Philippines.

  13. Results Top 10 provinces/HUCs with high estimates of yound adult obesity prevalence

  14. Summary and Conclusions • The Poisson regression with spatially autocorrelated random effects produced reliable estimates of the prevalence of young adult obesity in each province and highly urbanized city. • Majority of the provinces and HUCs have estimates within 0% to 4% which is lower than the obtained national estimate of 4.5%. • Batanes, Siquijor and Camiguin are the top 3 provinces with highest prevalence of young adult obesity. The high prevalence rate observed may be due to the lack of access to health centers and high consumption of highly-processed and energy-dense foods. • Among the provinces with high estimates of count and prevalence of young adult obesity are Iligan City, Biliran, Mountain Province, San Juan City and Davao del Sur

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