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Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data.

Hoffman K, Aschengrau A, Webster TF, Bartell SM, Vieira VM - BMC Public Health (2015)

Bottom Line: We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03).Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82).However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

View Article: PubMed Central - PubMed

Affiliation: Nicholas School of the Environment, Duke University, Durham, NC, USA. kate.hoffman@duke.edu.

ABSTRACT

Background: Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location.

Methods: We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk.

Results: We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82).

Conclusion: Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

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Related in: MedlinePlus

Geographic distribution of depression vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes. The scale includes most, but not all, observed odds ratios
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Fig2: Geographic distribution of depression vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes. The scale includes most, but not all, observed odds ratios

Mentions: Before adjustment for spatial confounding, we observed statistically significant geographic variation in the odds of depression for children born to women living on upper Cape Cod between 1969 and 1983. Children born in Mashpee and portions of northern Barnstable were approximately 1.75 to 2.50 times as likely to be diagnosed with depression compared to children born in the study area as a whole (Table 2; Fig. 2a). Conversely, children born in Bourne, Sandwich, and southern portions of Barnstable had lower odds of depression. Adjusting for spatial confounding slightly decreased the size of areas of increased and decreased odds; however, results continued to suggest spatial variation in the odds of depression, particularly in in areas of Mashpee and Barnstable (Fig. 2b). Prior to adjustment for spatial confounding, we observed a similar pattern for PTSD, with increased odds in Mashpee and portions of Barnstable compared to the study area as a whole. In Mashpee, however, the pattern appeared to be driven by a greater proportion of participants with a family history of mental illness living in the area (Fig. 3a). After adjustment for family history and other confounders, the optimal span size increased from 20 to 95 % of the data and the global deviance statistic, which was statistically significant in the crude model (P = 0.01), was no longer significant (P = 0.80; Table 2; Fig. 3b). Similarly, as expected with the increased optimal span size, the range of odds ratios was much narrower across the study area following adjustment (adjusted odds ratio (OR) range: 0.49 to 1.36 across the study area compared to crude OR range: 0.07–3.50). In general, after adjustment for spatial confounding, the odds of PTSD were slightly decreased in northern portions of the study area and slightly increased in southern portions. We did not find evidence of spatial variation in the risk of bipolar disorder in either the unadjusted or adjusted models. Like the adjusted PTSD analyses, the odds of bipolar disorder were lower in northern portions of the study area and slightly increased in southern portions of Barnstable (Table 2; Fig. 4).Table 2


Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data.

Hoffman K, Aschengrau A, Webster TF, Bartell SM, Vieira VM - BMC Public Health (2015)

Geographic distribution of depression vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes. The scale includes most, but not all, observed odds ratios
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4508761&req=5

Fig2: Geographic distribution of depression vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes. The scale includes most, but not all, observed odds ratios
Mentions: Before adjustment for spatial confounding, we observed statistically significant geographic variation in the odds of depression for children born to women living on upper Cape Cod between 1969 and 1983. Children born in Mashpee and portions of northern Barnstable were approximately 1.75 to 2.50 times as likely to be diagnosed with depression compared to children born in the study area as a whole (Table 2; Fig. 2a). Conversely, children born in Bourne, Sandwich, and southern portions of Barnstable had lower odds of depression. Adjusting for spatial confounding slightly decreased the size of areas of increased and decreased odds; however, results continued to suggest spatial variation in the odds of depression, particularly in in areas of Mashpee and Barnstable (Fig. 2b). Prior to adjustment for spatial confounding, we observed a similar pattern for PTSD, with increased odds in Mashpee and portions of Barnstable compared to the study area as a whole. In Mashpee, however, the pattern appeared to be driven by a greater proportion of participants with a family history of mental illness living in the area (Fig. 3a). After adjustment for family history and other confounders, the optimal span size increased from 20 to 95 % of the data and the global deviance statistic, which was statistically significant in the crude model (P = 0.01), was no longer significant (P = 0.80; Table 2; Fig. 3b). Similarly, as expected with the increased optimal span size, the range of odds ratios was much narrower across the study area following adjustment (adjusted odds ratio (OR) range: 0.49 to 1.36 across the study area compared to crude OR range: 0.07–3.50). In general, after adjustment for spatial confounding, the odds of PTSD were slightly decreased in northern portions of the study area and slightly increased in southern portions. We did not find evidence of spatial variation in the risk of bipolar disorder in either the unadjusted or adjusted models. Like the adjusted PTSD analyses, the odds of bipolar disorder were lower in northern portions of the study area and slightly increased in southern portions of Barnstable (Table 2; Fig. 4).Table 2

Bottom Line: We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03).Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82).However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

View Article: PubMed Central - PubMed

Affiliation: Nicholas School of the Environment, Duke University, Durham, NC, USA. kate.hoffman@duke.edu.

ABSTRACT

Background: Mental health disorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location.

Methods: We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969-1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk.

Results: We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61-3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49-1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58-1.17, P = 0.82).

Conclusion: Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.

Show MeSH
Related in: MedlinePlus