Literature DB >> 35861297

Clustering of Social Determinants of Health Among Patients.

Nicholas K Schiltz1, Kevin Chagin2, Ashwini R Sehgal2.   

Abstract

INTRODUCTION/
OBJECTIVES: Many health systems screen patients for social determinants of health and refer patients with social needs to community organizations for assistance. Understanding how social determinants cluster together may help guide assistance programs.
METHODS: This study examined patients screened by The MetroHealth System in Cleveland, Ohio for 9 social determinants, including food insecurity, financial strain, transportation limitations, inability to pay for housing or utilities, intimate partner violence, social isolation, infrequent physical activity, daily stress, and lack of internet access. Clustering analyses were performed to determine which combination of social determinants occurred together more often than would be expected if each determinant were independent of each other.
RESULTS: Among 23 161 screened patients, there were 19 dyads, 13 triads, and one tetrad of social determinants that clustered together. The most prevalent triad of food insecurity, social isolation, and inability to pay for housing or utilities occurred among 1095 patients but would be expected to occur among 284 patients, for an observed/expected ratio of 3.85 (95% confidence interval 3.64-4.07). In multivariate analyses, younger, Black, and lower income patients were 2 to 3 times more likely to have this triad compared to older, White, and wealthier patients.
CONCLUSIONS: Social determinants of health frequently cluster together, and such clustering is associated with patient demographic characteristics. Further work is needed to determine how social determinant clusters impact health and cost outcomes and to develop programs that can address multiple co-existing social needs.

Entities:  

Keywords:  clustering; patients; social determinants of health

Mesh:

Year:  2022        PMID: 35861297      PMCID: PMC9310337          DOI: 10.1177/21501319221113543

Source DB:  PubMed          Journal:  J Prim Care Community Health        ISSN: 2150-1319


Introduction

Because social determinants influence healthcare cost, quality, and other outcomes, many health systems are screening patients for social needs and referring them to community service organizations for assistance. Topics addressed in screening may include food, housing, transportation, utilities, and exposure to interpersonal violence. Numerous research studies have been published describing these efforts.[2 -4] By contrast, less is known about how social determinants of health cluster together. Understanding such clustering may help guide assistance programs if patients with multiple social determinants require more intensive or different services. A qualitative study found that having multiple social needs exacerbated chronic illnesses, reduced engagement with health care, and created a sense of disempowerment, isolation, depression, and stigmatization. This study sought to examine how social determinants of health cluster together among patients of The MetroHealth System, a large safety-net health system in Cleveland, Ohio. The study also examines how demographic factors, including age, sex, race, ethnicity, and income, correlate with clustering.

Methods

In 2019, the MetroHealth System Institute for Health, Opportunity, Partnership, and Empowerment initiated a program to systematically screen patients for social determinants of health and refer patients with social needs to a network of approximately 140 community service organizations for assistance. Screening occurred (1) in-person or by telephone through contact with a care coordinator or other staff person or (2) online through a MyChart patient portal questionnaire triggered by an appointment for a primary care, OB-GYN, or geriatrics visit. The screening questionnaire asked about 9 topics, including food insecurity, financial strain, transportation limitations, inability to pay for housing or utilities, intimate partner violence, social isolation, infrequent physical activity, daily stress, and lack of internet access. The questions were obtained from previously validated surveys. This study reports on results from patients screened between May 2019 and September 2021. Pre-defined criteria for being at risk for each social determinant were used to categorize questionnaire responses. For example, patients who answered often or sometimes to either of the 2 food security questions were categorized as being food insecure. Patient demographic variables (age, gender, self-reported race/ethnicity, home address) were obtained from electronic medical records. Census data were used to determine the median annual income for each patient’s census tract. This study was approved by the Institutional Review Board of the MetroHealth System. Association rule mining was used to identify combinations of social determinants of health that co-occurred together. Association rule mining is a machine learning method originally developed to find items commonly purchased together in the same transaction, but has since been extended to other applications, including health and medicine.[6,7] All clusters of social determinants that occurred in at least 2% of the study population were identified. For each cluster, the observed/expected ratio was calculated as the observed count divided by the expected count of the cluster if each social determinant within the cluster were statistically independent of each other. For example, if 20% of patients are unable to pay for housing or utilities and 40% have social isolation, then 8% (20% × 4 0%) would be expected to have both determinants if they were independent of each other. Next, a multivariable log-binomial regression model was fitted for each cluster, with the presence of the cluster as the dependent variable, and age, gender, race, ethnicity and income as independent variables to estimate adjusted prevalence ratios and 95% confidence intervals. Unadjusted prevalence ratios were estimated similarly, but with each independent variable modeled separately. All analyses were conducted using R version 4.1.2 (Vienna, Austria) and the R package “arules” version 1.7.3.

Results

A total of 23 161 patients completed the screening questionnaire during the study period. The mean age of screened patients was 51 years, a majority were female, and most were White or Black (Table 1). The most common social determinants of health were social isolation, infrequent physical activity, and inability to pay for housing or utilities. Of the 23 161 patients, 34.5% had no social determinants of health, 31.1% had only one determinant, 18.2% had 2 determinants, 8.5% had 3 determinants, and 7.6% had 4 or more determinants.
Table 1.

Characteristics of Screened Patients (n = 23 161).*

Age, years51.0 (18.2)
Female16 005 (69.1%)
Race
 White15 303 (66.1%)
 Black5881 (25.4%)
 Missing1242 (5.4%)
 Other race735 (3.2%)
Ethnicity
 Non-Hispanic20 869 (90.1%)
 Hispanic1405 (6.1%)
 Missing887 (3.8%)
Annual income
 Less than $24 9997247 (31.9%)
 $25 000-$29 9994372 (19.2%)
 $30 000-$34 9993891 (17.1%)
 $35 000 or higher7243 (31.8%)
 Missing408 (1.8%)
Social determinants of health
 Food insecurity3740 (16.1%)
 Financial strain1180 (5.1%)
 Transportation limitations1272 (5.5%)
 Unable to pay for housing or utilities4438 (19.2%)
 Intimate partner violence806 (3.5%)
 Social isolation9192 (39.7%)
 Infrequent physical activity4574 (19.7%)
 Daily stress4334 (18.7%)
 Lack of internet access350 (1.5%)
Total number of social determinants
 None7996 (34.5%)
 17208 (31.1%)
 24220 (18.2%)
 31973 (8.5%)
 4 or more1764 (7.6%)

Results are number (percentage) for categorical variables and mean (standard deviation) for continuous variables.

Characteristics of Screened Patients (n = 23 161).* Results are number (percentage) for categorical variables and mean (standard deviation) for continuous variables. Many social determinants occurred together more often than if each determinant were independent of each other. There were 19 dyads, 13 triads, and 1 tetrad of social determinants that were present among more than 2% of patients (Table 2). The most prevalent triad (food insecurity, social isolation, and inability to pay for housing or utilities) occurred among 1095 patients but would be expected to occur among 284 patients, for an observed/expected ratio of 3.85 (95% confidence interval 3.64-4.07). Clusters with particularly high observed/expected ratios included the triad of financial strain, food insecurity, and housing or utilities (ratio 16.54); the triad of food insecurity, transportation, and housing or utilities (ratio 13.52); the triad of financial strain, food insecurity, and daily stress (ratio 14.39); and the tetrad of food insecurity, social isolation, daily stress, and housing or utilities (ratio 9.92).
Table 2.

Combination of Social Determinants of Health Present Among More Than 2% of Patients.

CombinationNumber of patients (%)Observed/Expected (95% confidence interval)
Dyads
 Physical activity, Social isolation2354 (10.2)1.30 (1.25-1.34)
 Social isolation, Daily stress2294 (9.9)1.33 (1.29-1.38)
 Food insecurity, Social isolation2130 (9.2)1.44 (1.38-1.49)
 Social isolation, Housing or Utilities2128 (9.2)1.21 (1.16-1.26)
 Food insecurity, Housing or Utilities1909 (8.2)2.66 (2.56-2.77)
 Food insecurity, Daily stress1397 (6.0)2.00 (1.90-2.10)
 Daily stress, Housing or Utilities1275 (5.5)1.54 (1.46-1.62)
 Physical activity, Daily stress1158 (5.0)1.35 (1.28-1.43)
 Physical activity, Housing or Utilities1048 (4.5)1.20 (1.13-1.27)
 Food insecurity, Physical activity972 (4.2)1.32 (1.24-1.40)
 Financial strain. Food insecurity883 (3.8)4.63 (4.35-4.94)
 Food insecurity, Transportation limitations809 (3.5)3.94 (3.68-4.21)
 Social isolation, Transportation limitations773 (3.3)1.53 (1.43-1.64)
 Financial strain, Housing or Utilities729 (3.1)3.22 (3.00-3.46)
 Financial strain, Social isolation699 (3.0)1.49 (1.39-1.60)
 Transportation limitations, Housing or Utilities693 (3.0)2.84 (2.64-3.06)
 Financial strain, Daily stress644 (2.8)2.92 (2.71-3.14)
 Daily stress, Transportation limitations558 (2.4)2.34 (2.16-2.54)
 Intimate partner violence, Social isolation481 (2.1)1.50 (1.38-1.64)
Triads
 Food insecurity, Social isolation, Housing or Utilities1095 (4.7)3.85 (3.64-4.07)
 Food insecurity, Social isolation, Daily stress922 (4.0)3.32 (3.12-3.53)
 Food insecurity, Daily stress, Housing or Utilities779 (3.4)5.81 (5.43-6.22)
 Social isolation, Daily stress, Housing or Utilities777 (3.4)2.36 (2.20-2.52)
 Physical activity, Social isolation Daily stress695 (3.0)2.05 (1.90-2.20)
 Food insecurity, Physical activity Social isolation623 (2.7)2.13 (1.97-2.29)
 Financial strain, Food insecurity, Housing or Utilities604 (2.6)16.54 (15.30-17.88)
 Physical activity, Social isolation, Housing or Utilities587 (2.5)1.69 (1.56-1.83)
 Financial strain, Food insecurity, Social isolation546 (2.4)7.22 (6.65-7.84)
 Food insecurity, Transportation limitations, Housing or Utilities532 (2.3)13.52 (12.44-14.69)
 Food insecurity, Social isolation, Transportation limitations519 (2.2)6.37 (5.85-6.93)
 Financial strain, Food insecurity, Daily stress513 (2.2)14.39 (13.22-15.66)
 Food insecurity, Physical activity, Housing or Utilities512 (2.2)3.62 (3.32-3.94)
Tetrads
 Food insecurity, Social isolation, Daily stress, Housing or Utilities528 (2.3)9.92 (9.13-10.78)
Combination of Social Determinants of Health Present Among More Than 2% of Patients. In multivariate analyses, younger, Black, and lower income patients were 2 to 3 times more likely to have the triad of food insecurity, social isolation, and daily stress compared to older, White, and wealthier patients (Table 3). Patients residing in census tracts with median annual incomes <$25 000 were 3.43 (95% confidence interval 2.83-4.20) times more likely than patients residing in census tracts with median annual incomes ≥$35 000 to have this triad. Results for multivariate analyses of demographic correlates of all clusters are included in the Appendix.
Table 3.

Demographic Correlates of a Specific Combination of Social Determinants of Health (Triad of Food Insecurity, Social Isolation, Housing or Utilities).

Triad present n (%)Triad absent n (%)Unadjusted prevalence ratio (95% confidence interval)Adjusted prevalence ratio (95% confidence interval)
Number of patientsn = 1095n = 22 066
Age
 <30 years253 (23.1)3811 (17.3)2.11 (1.77-2.50)1.79 (1.50-2.14)
 30-44 years308 (28.1)5016 (22.8)1.96 (1.66-2.31)1.86 (1.58-2.19)
 45-59291 (26.6)5241 (23.8)1.78 (1.51-2.10)1.68 (1.42-1.99)
 ≥60 years243 (22.2)7977 (36.2)ReferenceReference
Gender
 Female789 (72.1)15 216 (69.0)1.15 (1.01-1.31)0.94 (0.82-1.07)
 Male306 (27.9)6850 (31.0)ReferenceReference
Race
 Black519 (47.4)5362 (24.3)2.87 (2.54-3.24)1.85 (1.62-2.12)
 White471 (43.0)14 832 (67.2)ReferenceReference
Ethnicity
 Hispanic103 (9.4)1302 (5.9)1.61 (1.31-1.95)1.23 (0.96-1.55)
 Non-Hispanic951 (86.8)19 918 (90.3)ReferenceReference
Income
 Less than $25 000632 (59.1)6615 (30.5)4.79 (3.99-5.78)3.43 (2.83-4.20)
 $25 000-$29 999209 (19.6)4163 (19.2)2.62 (2.12-3.26)2.35 (1.90-2.92)
 $30 000-$34 99996 (9.0)3795 (17.5)1.35 (1.04-1.75)1.29 (0.99-1.67)
 $35 000 or higher132 (12.3)7111 (32.8)ReferenceReference
Appendix.

Results for Multivariate Analyses of Demographic Correlates of All Clusters.

ClusterBlackHispanicFemaleIncome <25KIncome 25-29Income 30-34Age < 30Age 30-44Age 45-59
Physical Activity & Social Isolation1.06 (0.97-1.17)1.39 (1.19-1.63)1.15 (1.05-1.25)2.08 (1.86-2.33)1.70 (1.51-1.92)1.31 (1.14-1.50)0.77 (0.69-0.86)0.74 (0.67-0.82)0.71 (0.64-0.78)
Social Isolation & Daily Stress0.86 (0.78-0.95)1.09 (0.93-1.27)1.19 (1.08-1.30)1.74 (1.56-1.94)1.50 (1.33-1.68)1.24 (1.09-1.41)3.02 (2.67-3.40)2.54 (2.26-2.86)1.85 (1.63-2.10)
Food Insecurity & Social Isolation1.44 (1.31-1.59)1.49 (1.28-1.74)0.93 (0.85-1.02)2.93 (2.57-3.34)2.24 (1.94-2.58)1.30 (1.09-1.53)1.68 (1.49-1.89)1.49 (1.33-1.67)1.43 (1.28-1.60)
Social Isolation & Housing Utilities1.69 (1.54-1.86)1.12 (0.93-1.34)0.87 (0.79-0.95)2.45 (2.16-2.78)1.76 (1.53-2.03)1.25 (1.07-1.47)1.30 (1.15-1.46)1.34 (1.20-1.49)1.26 (1.13-1.40)
Food Insecurity & Housing Utilities2.04 (1.84-2.26)1.23 (1.03-1.47)1.00 (0.90-1.10)2.99 (2.59-3.46)2.15 (1.84-2.52)1.41 (1.18-1.70)1.51 (1.33-1.72)1.55 (1.37-1.75)1.59 (1.41-1.79)
Food Insecurity & Daily Stress1.20 (1.06-1.35)1.25 (1.03-1.53)1.25 (1.10-1.41)2.71 (2.31-3.18)2.15 (1.81-2.55)1.41 (1.16-1.72)2.59 (2.20-3.05)2.40 (2.05-2.80)2.25 (1.92-2.63)
Daily Stress & Housing Utilities1.40 (1.24-1.59)1.08 (0.86-1.35)1.20 (1.05-1.36)2.34 (1.98-2.75)1.72 (1.44-2.07)1.41 (1.16-1.72)2.46 (2.07-2.92)2.60 (2.21-3.06)2.21 (1.87-2.61)
Physical Activity & Daily Stress1.01 (0.88-1.16)1.29 (1.03-1.62)1.69 (1.46-1.95)1.93 (1.63-2.28)1.80 (1.51-2.15)1.37 (1.13-1.66)1.32 (1.11-1.57)1.60 (1.37-1.87)1.54 (1.31-1.80)
Physical Activity & Housing Utilities1.85 (1.61-2.12)1.33 (1.04-1.72)1.09 (0.95-1.25)2.54 (2.10-3.07)2.04 (1.66-2.50)1.44 (1.14-1.82)0.81 (0.67-0.97)0.90 (0.76-1.06)1.11 (0.96-1.30)
Food Insecurity & Physical Activity1.61 (1.39-1.86)1.90 (1.52-2.38)1.33 (1.15-1.55)3.59 (2.90-4.44)2.68 (2.13-3.37)1.62 (1.24-2.11)1.01 (0.84-1.21)1.02 (0.86-1.21)1.27 (1.08-1.50)
Financial Strain & Food Insecurity1.21 (1.04-1.42)1.08 (0.83-1.41)0.96 (0.83-1.11)3.43 (2.79-4.22)2.08 (1.65-2.63)1.33 (1.02-1.74)1.94 (1.59-2.36)1.72 (1.42-2.08)1.94 (1.62-2.34)
Food Insecurity & Transportation1.82 (1.55-2.14)1.31 (1.01-1.71)0.92 (0.79-1.07)3.45 (2.74-4.34)2.10 (1.62-2.71)1.38 (1.03-1.86)2.52 (2.08-3.06)1.54 (1.25-1.89)1.53 (1.25-1.88)
Social Isolation & Transportation1.65 (1.40-1.94)1.44 (1.10-1.88)0.94 (0.80-1.10)3.61 (2.85-4.58)2.31 (1.78-3.01)1.62 (1.20-2.17)2.30 (1.90-2.79)1.39 (1.13-1.71)1.22 (0.99-1.51)
Financial Strain & Housing Utilities1.56 (1.32-1.84)1.06 (0.78-1.45)1.00 (0.85-1.18)3.14 (2.49-3.95)1.97 (1.52-2.55)1.38 (1.03-1.84)1.95 (1.56-2.44)2.08 (1.68-2.56)2.03 (1.65-2.50)
Financial Strain & Social Isolation1.16 (0.98-1.39)1.26 (0.94-1.68)1.04 (0.88-1.23)3.01 (2.40-3.78)1.90 (1.48-2.45)1.31 (0.98-1.75)1.98 (1.58-2.48)1.92 (1.55-2.38)1.92 (1.55-2.38)
Transportation & Housing Utilities2.10 (1.76-2.50)1.42 (1.06-1.89)0.95 (0.80-1.13)3.90 (2.99-5.07)2.17 (1.61-2.92)1.63 (1.18-2.27)2.60 (2.09-3.23)1.83 (1.46-2.29)1.77 (1.41-2.21)
Financial Strain & Daily Stress1.03 (0.86-1.24)1.13 (0.83-1.54)1.19 (0.99-1.43)2.61 (2.08-3.29)1.73 (1.34-2.23)1.33 (1.00-1.76)2.66 (2.06-3.42)2.69 (2.11-3.43)2.82 (2.22-3.58)
Daily Stress & Transportation1.68 (1.38-2.04)1.13 (0.81-1.58)1.10 (0.90-1.34)2.49 (1.91-3.24)2.02 (1.52-2.69)1.66 (1.22-2.26)3.87 (3.00-4.99)2.38 (1.83-3.11)2.08 (1.58-2.72)
Intimate Partner Violence & Social Isolation1.36 (1.10-1.67)1.47 (1.06-2.05)1.33 (1.05-1.67)2.35 (1.80-3.08)1.66 (1.23-2.25)1.26 (0.90-1.76)10.91 (7.31-16.28)9.35 (6.29-13.92)4.40 (2.87-6.72)
Food Insecurity & Social Isolation & Housing Utilities1.85 (1.62-2.12)1.23 (0.96-1.56)0.94 (0.82-1.07)3.43 (2.82-4.18)2.35 (1.89-2.92)1.29 (1.00-1.68)1.79 (1.50-2.14)1.86 (1.57-2.19)1.68 (1.42-1.99)
Food Insecurity & Social Isolation & Daily Stress1.14 (0.99-1.33)1.29 (1.01-1.65)1.19 (1.02-1.39)3.24 (2.63-3.98)2.54 (2.03-3.16)1.43 (1.10-1.85)2.86 (2.34-3.50)2.55 (2.09-3.11)2.24 (1.83-2.74)
Food Insecurity & Daily Stress & Housing Utilities1.52 (1.29-1.79)1.01 (0.75-1.36)1.33 (1.12-1.58)3.03 (2.42-3.80)2.23 (1.74-2.85)1.45 (1.09-1.92)2.67 (2.13-3.36)2.85 (2.30-3.54)2.46 (1.97-3.07)
Social Isolation & Daily Stress & Housing Utilities1.44 (1.22-1.69)1.00 (0.75-1.35)1.25 (1.06-1.49)2.94 (2.35-3.68)2.09 (1.64-2.67)1.51 (1.15-1.99)2.65 (2.12-3.32)2.90 (2.35-3.59)2.07 (1.66-2.59)
Physical Activity & Social Isolation & Daily Stress0.97 (0.81-1.16)1.29 (0.96-1.72)1.67 (1.38-2.02)2.46 (1.96-3.09)2.06 (1.62-2.62)1.65 (1.27-2.14)1.60 (1.28-2.01)1.84 (1.50-2.27)1.60 (1.29-1.97)
Food Insecurity & Physical Activity & Social Isolation1.49 (1.25-1.79)1.98 (1.50-2.62)1.27 (1.05-1.53)3.98 (3.02-5.24)2.95 (2.20-3.95)1.65 (1.17-2.32)1.15 (0.91-1.45)1.26 (1.02-1.57)1.40 (1.13-1.72)
Financial Strain & Food Insecurity & Housing Utilities1.48 (1.23-1.78)1.10 (0.79-1.53)1.04 (0.86-1.24)3.51 (2.71-4.55)2.09 (1.56-2.79)1.37 (0.98-1.91)2.23 (1.74-2.87)2.22 (1.75-2.82)2.17 (1.72-2.75)
Physical Activity & Social Isolation & Housing Utilities1.62 (1.34-1.95)1.25 (0.89-1.76)1.15 (0.95-1.38)3.39 (2.58-4.45)2.49 (1.86-3.34)1.61 (1.15-2.25)0.96 (0.75-1.22)1.17 (0.94-1.45)1.17 (0.94-1.45)
Financial Strain & Food Insecurity & Social Isolation1.14 (0.94-1.39)1.19 (0.86-1.64)1.02 (0.84-1.24)3.70 (2.83-4.84)2.09 (1.55-2.82)1.30 (0.91-1.84)2.19 (1.70-2.82)1.89 (1.47-2.42)1.98 (1.55-2.53)
Food Insecurity & Transportation & Housing Utilities2.01 (1.65-2.46)1.24 (0.89-1.74)0.91 (0.75-1.10)3.99 (2.97-5.37)2.10 (1.50-2.95)1.43 (0.97-2.10)3.05 (2.37-3.92)1.94 (1.49-2.52)1.83 (1.40-2.38)
Food Insecurity & Social Isolation & Transportation1.76 (1.44-2.15)1.44 (1.03-2.00)0.87 (0.72-1.06)3.95 (2.93-5.32)2.34 (1.68-3.27)1.44 (0.98-2.11)2.62 (2.05-3.34)1.57 (1.21-2.03)1.51 (1.17-1.96)
Financial Strain & Food Insecurity & Daily Stress1.01 (0.82-1.24)1.02 (0.72-1.45)1.19 (0.97-1.45)3.20 (2.45-4.18)1.99 (1.48-2.67)1.39 (0.99-1.94)2.78 (2.09-3.71)2.84 (2.16-3.74)2.98 (2.27-3.91)
Food Insecurity & Physical Activity & Housing Utilities1.95 (1.59-2.39)1.39 (0.98-1.96)1.29 (1.05-1.59)4.12 (3.00-5.65)2.82 (2.00-3.97)1.97 (1.35-2.88)1.35 (1.04-1.75)1.48 (1.16-1.89)1.64 (1.29-2.07)
Food Insecurity & Social Isolation & Daily Stress & Housing Utilities1.49 (1.22-1.81)0.94 (0.65-1.36)1.35 (1.09-1.67)3.63 (2.72-4.85)2.63 (1.93-3.59)1.51 (1.05-2.17)2.87 (2.17-3.80)3.11 (2.38-4.06)2.41 (1.83-3.18)
Demographic Correlates of a Specific Combination of Social Determinants of Health (Triad of Food Insecurity, Social Isolation, Housing or Utilities).

Discussion

This cross-sectional study found that social determinants of health frequently cluster together, particularly among younger, minority, and lower income patients. These findings are consistent with previous work indicating that sizeable numbers of patients have more than 1 social determinant. A study based on the National Health and Nutrition Examination Survey (NHANES) concluded that 25% of American adults had 1 social determinant while 30% had 2 or more determinants. Another study of incident stroke estimated that about 7400 participants had 1 social determinant while 12 000 had 2 or more determinants. A novel aspect of our study is identifying clusters of social determinants that occur together more often than would be expected if each determinant were independent of each other. Other strengths of our study include a large sample size; inclusion of substantial numbers of White, Black, and Hispanic patients; and use of standardized questions assessing 9 different social determinants. Viewing social determinants in isolation may lead to interventions that are most appropriate to the subset of patients who have a single social need. However, simply bundling interventions for multiple social needs may not work unless interactions among clustered determinants are better understood. For example, interventions to improve social isolation may cause harm if a patient is also experiencing intimate partner violence. By contrast, the triad of physical inactivity, social isolation, and daily stress may be addressable with a single intervention such as joining a group physical activity. Health systems and community service organizations should determine how to tailor assistance for patients with specific clusters of social determinants. Researchers should determine the impact of clustering on health and cost outcomes. A study of lumbar spine surgery patients found that specific clusters of social determinants were associated with decreased pain and increased satisfaction and quality of life. Several limitations must be considered in interpreting these results. This study focused on a single health care system, relied on self-reported data, and used census tracts to estimate annual income. Patients with difficulties such as transportation limitations or lack of internet access may have been less likely to participate in in-person or online screening for social determinants of health. The COVID-19 pandemic likely influenced some social determinants such as social isolation. In conclusion, social determinants of health frequently cluster together, and such clustering is associated with patient demographic characteristics. Further work is needed i) to determine how social determinant clusters impact health and cost outcomes and ii) to develop programs that can address multiple co-existing social needs.
  11 in total

1.  Precarity and health: Theorizing the intersection of multiple material-need insecurities, stigma, and illness among women in the United States.

Authors:  Henry J Whittle; Anna M Leddy; Jacqueline Shieh; Phyllis C Tien; Ighovwerha Ofotokun; Adaora A Adimora; Janet M Turan; Edward A Frongillo; Bulent Turan; Sheri D Weiser
Journal:  Soc Sci Med       Date:  2019-11-16       Impact factor: 4.634

2.  High-Risk Comorbidity Combinations in Older Patients Undergoing Emergency General Surgery.

Authors:  Vanessa P Ho; Nicholas K Schiltz; Andrew P Reimer; Elizabeth A Madigan; Siran M Koroukian
Journal:  J Am Geriatr Soc       Date:  2018-12-02       Impact factor: 5.562

3.  Association rules and data mining in hospital infection control and public health surveillance.

Authors:  S E Brossette; A P Sprague; J M Hardin; K B Waites; W T Jones; S A Moser
Journal:  J Am Med Inform Assoc       Date:  1998 Jul-Aug       Impact factor: 4.497

4.  Prevalence of Social Determinants of Health and Associations of Social Needs Among United States Adults, 2011-2014.

Authors:  Eun Ji Kim; Sara Abrahams; Omolara Uwemedimo; Joseph Conigliaro
Journal:  J Gen Intern Med       Date:  2019-11-20       Impact factor: 5.128

5.  Implementing an EHR-based Screening and Referral System to Address Social Determinants of Health in Primary Care.

Authors:  Pablo Buitron de la Vega; Stephanie Losi; Linda Sprague Martinez; Allison Bovell-Ammon; Arvin Garg; Thea James; Alana M Ewen; Marna Stack; Heloisa DeCarvalho; Megan Sandel; Rebecca G Mishuris; Stella Deych; Patrick Pelletier; Nancy R Kressin
Journal:  Med Care       Date:  2019-06       Impact factor: 2.983

6.  Impact of Multiple Social Determinants of Health on Incident Stroke.

Authors:  Evgeniya Reshetnyak; Mariella Ntamatungiro; Laura C Pinheiro; Virginia J Howard; April P Carson; Kimberly D Martin; Monika M Safford
Journal:  Stroke       Date:  2020-07-16       Impact factor: 10.170

7.  Assessment of Social Risk Factors and Interest in Receiving Health Care-Based Social Assistance Among Adult Patients and Adult Caregivers of Pediatric Patients.

Authors:  Emilia H De Marchis; Danielle Hessler; Caroline Fichtenberg; Eric W Fleegler; Amy G Huebschmann; Cheryl R Clark; Alicia J Cohen; Elena Byhoff; Mark J Ommerborn; Nancy Adler; Laura M Gottlieb
Journal:  JAMA Netw Open       Date:  2020-10-01

8.  A Framework for Evaluating Social Determinants of Health Screening and Referrals for Assistance.

Authors:  Kevin Chagin; Franklin Choate; Karen Cook; Susan Fuehrer; James E Misak; Ashwini R Sehgal
Journal:  J Prim Care Community Health       Date:  2021 Jan-Dec

9.  Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio.

Authors:  Aluísio J D Barros; Vânia N Hirakata
Journal:  BMC Med Res Methodol       Date:  2003-10-20       Impact factor: 4.615

10.  Quantifying the collective influence of social determinants of health using conditional and cluster modeling.

Authors:  Zachary D Rethorn; Alessandra N Garcia; Chad E Cook; Oren N Gottfried
Journal:  PLoS One       Date:  2020-11-05       Impact factor: 3.240

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