Dataset Information

The spatial distribution of overweight and obesity among a birth cohort of young adult Filipinos (Cebu Philippines, 2005): an application of the Kulldorff spatial scan statistic.

ABSTRACT:

Objectives

The objectives of the study were to test for spatial clustering of obesity in a cohort of young adults in the Philippines, to estimate the locations of any clusters, and to relate these to neighborhood-level urbanicity and individual-level socioeconomic status (SES).

Subjects

Data are from a birth cohort of young adult (mean age 22 years) Filipino males (n=988) and females (n=820) enrolled in the Cebu Longitudinal Health and Nutrition Survey.

Methods

We used the Kulldorff spatial scan statistic to detect clusters associated with unusually low or high prevalences of overweight or obesity (defined using body mass index, waist circumference and body fat percentage). Cluster locations were compared to neighborhood-level urbanicity, which was measured with a previously validated scale. Individual-level SES was adjusted for using a principal components analysis of household assets.

Results

High-prevalence clusters were typically centered in urban areas, but often extended into peri-urban and even rural areas. There were also differences in clustering by both sex and the measure of obesity used. Evidence of clustering in males, but not females, was much weaker after adjustment for SES.

SUBMITTER: Dahly DL

PROVIDER: S-EPMC3730219 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

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Publications

The spatial distribution of overweight and obesity among a birth cohort of young adult Filipinos (Cebu Philippines, 2005): an application of the Kulldorff spatial scan statistic.

Dahly D L DL Gordon-Larsen P P Emch M M Borja J J Adair L S LS

Nutrition & diabetes 20130701

<h4>Objectives</h4>The objectives of the study were to test for spatial clustering of obesity in a cohort of young adults in the Philippines, to estimate the locations of any clusters, and to relate these to neighborhood-level urbanicity and individual-level socioeconomic status (SES).<h4>Subjects</h4>Data are from a birth cohort of young adult (mean age 22 years) Filipino males (n=988) and females (n=820) enrolled in the Cebu Longitudinal Health and Nutrition Survey.<h4>Methods</h4>We used the ...[more]

PMID: 23817443

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Project description:BackgroundA common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics.ResultsThis research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases.ConclusionsThe GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.

Dataset Information

The spatial distribution of overweight and obesity among a birth cohort of young adult Filipinos (Cebu Philippines, 2005): an application of the Kulldorff spatial scan statistic.

Objectives

Subjects

Methods

Results

Publications

The spatial distribution of overweight and obesity among a birth cohort of young adult Filipinos (Cebu Philippines, 2005): an application of the Kulldorff spatial scan statistic.

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