Exeley Inc.

TRUONG, Thi-Cam-Trang

BUI, Manh-Ha

NGUYEN, Dang-Khoa

KOBAYASHI, Takaomi

FABRICATION AND CHARACTERISATION OF CHITOSAN/COCONUT FIBER COMPOSITE MEMBRANES FOR ELIMINATING CU2+ AND PB2+ FROM AQUEOUS SOLUTIONS

Maciejewska, Karina

Drzazga, Zofia

Differences in spatio-temporal distribution of the visual P3b event-related potential between young men and women

Zandi, Nazanin

Zaniani, Nosaibeh Riahi

Moghimi, Ali

Roohbakhsh, Ali

Protective effects of M8-B, a TRPM8 antagonist, on febrile- and pentylenetetrazol-induced seizures

CAMPOS-MÚZQUIZ, LIZETH GUADALUPE

MÉNDEZ-OLVERA, ESTELA TERESITA

ARELLANO-REYNOSO, BEATRIZ

MARTÍNEZ-GÓMEZ, DANIEL

Supplementary materials for the article: 
Campos-Múzquiz L.G. et al. Campylobacter fetus is internalized by bovine endometrial 
epithelial cells.  
Pol J Microbiol. 2019, Vol. 68, No 2, 217–224.
 
 
 
Fig. S1. Western blot of C. fetus proteins (lanes 2 to 4) and epithelial cells proteins from 
bovine endometrium (lanes 6 to 8). Lanes 1 and 5, PAGE ruler (Fermentas). Lanes 2 and 6, 
anti-C. fetus non-adsorbed serum. Lanes 3 and 7, anti-C. fetus adsorbed serum and lanes 4 
and 8, anti-rabbit HRP antibodies. 


Campylobacter fetus is Internalized by Bovine Endometrial Epithelial Cells

Młodzińska, Ewa

Hryniewicz, Waleria

English

QUALITY ASSURANCE IN THE MEDICAL MICROBIOLOGY LABORATORY

Drakonaki, Eleni E.

Sudoł-Szopińska, Iwona

Sinopidis, Christos

Givissis, Panagiotis

High resolution ultrasound for imaging complications of muscle injury: Is there an additional role for elastography?

Ocal, Osman

Baydar, Dilek Ertoy

Idilman, Ilkay Sedakat

Dogan, Hasan Serkan

Tekgul, Serdat

Ozmen, Mustafa

Sonographic diagnosis of large-cell calcifying Sertoli cell tumor

Jamali, Sanaa

Danse, Etienne

A developmental variant of the thyroid cartilage

Marcum, Christopher Steven

Koehly, Laura M.

 Journal of Social Structure:  Special Issue on Networks 
and Health  
Social Networks and Health:  Micro Processes and 
Macro Structures 
 
Christopher Steven Marcum, PhDa and Laura M. Koehly, 
PhDb 
 
Abstract 
 
Since its nascency, the field of social network analysis has been intrinsically linked to human 
health and well-being. In fact, the very first empirical article ever published in Sociometry 
evaluated a psychiatric treatment to inter-personal distress that employed the spontaneous 
interactions unfolding in a triad of physician, patient, and proxy actors (Moreno, 1937). This was 
a first attempt in a research context to show that there may be direct effects that tie patterns of 
social relations to individual well-being in small groups. Moreno & Jennings (1938) also made 
the early and astute argument that the social structure observed through measurement of social 
relations is inseparable from biological and psychological frames of reference: they are all 
inherently interdependent. More than 80 years of research in this area has since been developed 
and yet the field is still flush with opportunities to learn about the interplay between social 
networks and health. In this special issue of the Journal of Social Structure, we highlight the 
work of leading scientists in this field.  
___________ 
aNational Institutes of Health, chris.marcum@nih.gov 
bNational Institutes of Health, koehlyl@mail.nih.gov 
 
 
2 
 
Format of this Issue 
 
This special issue on networks and health represents a collection of papers by outstanding 
scholars invited by us to highlight novel, timely work in this increasingly large field. The idea for 
such an issue in the Journal of Social Structure grew out of proposals to use the journal to call 
attention to topical areas of social network analysis brought to the INSNA Business meeting of 
the 2015 Sunbelt meeting in Brighton, UK. We invited over a dozen researchers known to be 
leaders or emerging scholars doing work on a wide variety of health topics from various social 
network perspectives to submit abstracts and titles for consideration and review. The papers 
included here were reviewed by at least one of the contributing authors and two editors, as well 
as by one external reviewer when needed. The review process was single-blind, where the 
reviewers knew the names of the authors.  Thus, papers in this collection should be referenced as 
peer-reviewed chapters.  
 
In our consideration of whom to invite, we aimed for a breadth of both health topics and social 
network perspectives.  For the former, we encouraged work that has interventional, experimental, 
or policy applications.  Relevant health topics we received included network based childhood 
obesity interventions (de la Haye et al., this issue), network influences of clinician attitudes about 
electronic health records (Yuan et al., this issue), multiplex networks involved in HIV prevention 
engagement (Young et al., this issue), the co-evolution of friendship networks and mental health 
over time (Mundt & Zakletskaia, this issue), the diffusion of family health history knowledge 
(Hood et al., this issue), and finally the role of transitivity among infant-object-parent 
interactions in the risk for autism (Schleier et al., this issue). For the latter, the breadth of social 
network perspectives spanned the spectrum from entirely ego-centered to dyadic to triadic to 
whole network cross-sectional and longitudinal designs. The variability in the datasets and 
theoretical perspectives presented were complemented with equally varying analytic approaches, 
including network descriptives, generalized linear models, and stochastic actor oriented models. 
This is truly a holistic collection on health and social network research. 
 
We also directly encouraged senior authors to submit research that their students, trainees, and 
other emerging scholars played a role in producing.  Several of the submissions involved 
research on health disparity issues, including papers that focus on networks with ethnic, racial, 
gender and sexual minorities. Thus, the goals of this collection are aligned with those articulated 
by several key funding and professional organizations (e. g., National Institutes of Health, 
American Public Health Association) that seek to promote new areas of research on 
disadvantaged and minority populations in health while also providing opportunities for 
emerging Science, Technology, Engineering, and Math scholars to publish high quality research 
early in their careers.  
 
Naturally, with such an expansive hot topic that networks and health has become, we could not 
reasonably represent every aspect of this impressive field. In addition to the few topics 
comprising this issue, we also note that there is important social network research being done 
elsewhere in the areas of disease contagion (Manfredi & d’Onofrio, 2013), big data (including 
EHR and health sensor data sources a la Lienert et al., 2017 and Zeng et al., 2017), peer 
influence (Wang et al. 2018), and health knowledge generation (Hagel et al., 2017) among much 
other work.  In the balance of this editorial, we highlight the key themes and scientific 
3 
 
contributions, as well as identify several scientific priorities, that we have identified from the 
collection of papers in this issue. 
 
Key Themes and Scientific Contributions 
 
While rich in topical breadth, there were some unanticipated common themes among the 
contributed manuscripts. Foremost was the common use of mixed-methods research from very 
different perspectives. For instance, Hood et al. supplemented quantitative measurement and 
analysis of health communications in families with qualitative interview data describing the 
context of how and why certain health communication partners were preferred over others. Such 
approaches are becoming increasingly common in network analysis (Dominguez & Hollstein, 
2014; Suitor et al., 2017), especially in the context of health, where there is a need to understand 
more fully the motivations for the processes involved in networks. Importantly, such processes 
cannot be revealed by simple structure alone, thus, such mixed methods approaches are critical if 
the goal is to activate interpersonal ties via intervention.  
 
Indeed, much of the research comprising this collection provides evidence for designing 
interventions that may activate new interpersonal pathways or leverage established network ties 
(Valente, 2012; Shin et al., 2014). For example, Mundt and Zakletskaia (this issue) demonstrate 
the importance of interpersonal support systems for adolescents using psychological counseling 
services; their research highlights the importance of integrating group-based interventions in 
psychological counseling that focuses on building capabilities in social skills and developing 
social connections. In this case, building new interpersonal ties had important implications in 
adolescent mental health and social well-being.  In contrast, Yuan and colleagues (this issue) 
show that peer influence is stronger in stable network systems compared to those with notable 
churn.  Taken together, these two papers provide new insights on contexts in which intervention 
may focus on different aspects of social structure.  
 
Another common theme was a research emphasis on multiplexity with some papers explicitly 
studying multiple relationships and others employing them as secondary components of their 
analyses. Using the former approach, Young et al. (this issue) evaluated the role that multiple 
domains of interaction (personal confidant networks, sexual partnerships, online friendship, and 
online support group affiliation) work in combination to affect different sex behavior outcomes 
in a population of young black men who have sex with men.  This direct approach to 
multiplexity is complemented in the issue with implicit approaches, such as those taken by de la 
Haye et al. who evaluated how an intervention affected multiple types of health encouragement 
behaviors in families. Such interest in multiple relationships likely stem from the growing 
understanding of how human social networks involve multiple dimensions of interaction and that 
these dimensions, in isolation, as well as in combination, can have important implications for 
health.  
 
Scientific Priorities for Networks and Health 
 
From this collection, we see three primary priorities for the field.  The first is the need to dive a 
bit deeper and unravel how interpersonal mechanisms and social structure impact health. This 
4 
 
will likely require mixed-methods and multi-level approaches to fully understand the cognitive, 
psychological, social and behavioral mechanisms at play; this understanding is paramount for the 
development of effective interventions guided by network science. Second, ubiquitous 
technologies are resulting in data streams that capture some of these complexities, requiring the 
need for new methodological approaches to both integrate these data in meaningful ways.  Third, 
patterns of interaction that may arise from these digital footprints or, simply through observation, 
may help to identify those who are fragile or vulnerable for early intervention efforts. Key to 
success in this endeavor is identification of these patterns with translation to measurement 
protocols for use in practice. 
 
This is important because we know that social connections impact health. In a meta-analysis, 
Holt-Lunstad and colleagues (2010) demonstrated that social relationships, including limited 
social support resources and social isolation, contributed more to mortality than other factors, 
such as tobacco use, pollution, and being overweight.  What is not clear from this meta-analysis 
is the underlying mechanisms through which interpersonal ties impact health. Papers comprising 
this special issue aim to unravel some of these mechanisms - whether focused on micro 
processes characterized by triadic sequencing (for example, Schleier et al, this issue) or macro 
network structures (for example, Mundt and Zakletskaia, this issue). One could also imagine that 
social support mechanisms not only impact emotion-focused coping processes, but also enable 
and motivate engagement in healthy lifestyle behaviors - thus, impacting health through multiple 
avenues as a variation on multiplexity. This idea is consistent with de la Haye and colleagues’ 
(this issue) work investigating the role of encouragement on dietary behavior and, ultimately 
weight status, in at-risk families. We see unraveling how these interpersonal mechanisms impact 
health outcomes, and the various pathways through which that can happen, as an important 
continued avenue of inquiry.   
 
As new technologies provide for more data capturing on how humans engage with their 
environment, inclusive of both social and behavioral interactions, the network sciences have an 
important role to play. The challenges of integrating many sources of these micro-structural data 
in meaningful ways that connect such trajectories to health are an important opportunity for the 
field. This is particularly relevant with the advent of precision medicine and the All of Us 
initiative, where social and behavioral risk factors are key contributors to morbidity and 
mortality even after biological disposition is controlled for (Holt-Lunstad et al., 2010; Domingue 
et al., 2018). While a focus on ubiquitous technologies fits squarely in the “big data” space, 
capturing co-presence (Lienert et al., 2017), access to resources, and behavior, we do not want to 
lose sight of the importance of individual cognitions and perceptions of their social worlds which 
may be just as important as these digital footprints in influencing health. Indeed, as Yuan et al. 
point out in this issue, the emergence of new technologies themselves may offer opportunities to 
examine how perceptions shape and are shaped by connections in social networks over time. 
Thus, mixed methods approaches that integrate the “big data” with the deeper dive into 
understanding more fully the quality, structure, and function of these social interactions, 
potential institutional and cognitive barriers to access that go beyond geographic proximity to 
resources, and social-psychological factors that impact behavior are warranted.  We see such 
mixed methods approaches as important next steps in understanding how interpersonal 
mechanisms get ‘under the skin’ and impact health from very micro processes to macro 
structures. 
5 
 
 
For such interpersonal effects to manifest in clinical outcomes, efforts to tease out how to apply 
network approaches to interventions that affect, or otherwise reveal, disease trajectories are 
needed. Here too, contributors to this issue make headway. For instance, echoing the distant past 
history of using network analysis for clinical purposes referenced in our opening remarks, 
Schleier, et al. propose that the triad census can be employed to evaluate communicative ability 
in developmental milestones for young children. Through this work, those children most at risk 
can be identified earlier in their development, perhaps providing opportunity for earlier 
intervention efforts.  Such work represents not just innovation in measurement, but it also 
represents real movement towards clinical translation of network science.  
  
Finally, the emerging emphasis on precision and personalized medicine is likely to shift social 
network research on health. More work is needed to fully situate social contexts of health into 
this new paradigm. Specifically, the co-evolution of individual health outcomes with structural 
changes in social networks, along with the nested nature of biological and social data (Holt-
Lunstad, 2018), will need to be examined to fully appreciate the interplay between networks and 
health in manners that extend beyond the associational studies present in the literature (see, for 
some examples of both associational and predictive approaches in another special issue edited by 
Schaefer & adams, 2017). If social networks are part-and-parcel to personalized medicine, and 
we think they are, then recognition and funding support for additional longitudinal surveillance 
and theories of network influences on health are necessary. We fully expect that the scholars 
featured in this issue will be on the forefront of this endeavour.   
 
References 
 
Domingue, B. W., Belsky, D. W., Fletcher, J. M., Conley, D., Boardman, J. D., & Harris, K. M. 
(2018). The social genome of friends and schoolmates in the National Longitudinal Study 
of Adolescent to Adult Health. Proceedings of the National Academy of Sciences, 115(4), 
702-707. 
Dominguez, S. & B. Hollstein (2014) (Eds.): Mixed Methods Social Networks Research. Design 
and Applications. New York: Cambridge University Press. Structural Analysis in the 
Social Sciences Series; Series edited by Mark Granovetter. 
Hagel, C., Weidemann, F., Gauch, S., Edwards, S., & Tinnemann, P. (2017). Analysing 
published global Ebola Virus Disease research using social network analysis. PLoS 
Neglected Tropical Diseases, 11(10), e0005747. 
Holt-Lunstad, J. (2018). Why social relationships are important for physical health: a systems 
approach to understanding and modifying risk and protection. Annual review of 
psychology, 69, 437-458. 
Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010). Social relationships and mortality risk: a 
meta-analytic review. PLoS medicine, 7(7), e1000316. 
Lienert, J., Marcum, C. S., Finney, J., Reed-Tsochas, F., & Koehly, L. (2017). Social influence 
on 5-year survival in a longitudinal chemotherapy ward co-presence network. Network 
Science, 5(3), 308-327. 
Manfredi, P., & D'Onofrio, A. (Eds.). (2013). Modeling the interplay between human behavior 
and the spread of infectious diseases. Springer Science & Business Media: Berlin, 
Germany 
6 
 
Moreno, J.L. (1937). Inter-Personal Therapy and the Psychopathology of Inter-Personal 
Relations. Sociometry. 1(1/2), 9-76.  
Moreno, J.L. and Jennings, H.H. (1938). Statistics of Social Configurations. Sociometry. 1(3/4), 
342-374 
Schaefer, D. R., & adams, J. (2017). The coevolution of networks and health: Introduction to the 
Special Issue of Network Science. Network Science, 5(3), 249-256. 
Shin, H. S., Valente, T. W., Riggs, N. R., Huh, J., Spruijt‐Metz, D., Chou, C. P., & Ann Pentz, 
M. (2014). The interaction of social networks and child obesity prevention program 
effects: the pathways trial. Obesity, 22(6), 1520-1526. 
Suitor, J. J., Gilligan, M., Rurka, M., Con, G., Peng, S., & Pillemer, K. (2017). Conflict with 
Mothers and Siblings During Caregiving: Differential Costs for Black and White Adult 
Children. The Journals of Gerontology: Series B, 73(7), e86-e97.  
Valente, T. W. (2012). Network interventions. Science, 337(6090), 49-53. 
Wang, C., Hipp, J. R., Butts, C. T., & Lakon, C. M. (2018). The interdependence of cigarette, 
alcohol, and marijuana use in the context of school-based social networks. PloS one, 
13(7), e0200904. 
 
Zeng, L., Almquist, Z. W., & Spiro, E. S. (2017). Let's Workout! Exploring Social Exercise in an 
Online Fitness Community. iConference 2017 Proceedings Vol. 2. 
 


Social Networks and Health: Micro Processes and Macro Structures

LANDI, Stefania

RURAL LANDSCAPES OF THE 20TH CENTURY: FROM KNOWLEDGE TO PRESERVATION

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