Retrospective database analysis of cancer risk in patients with type 2 diabetes mellitus in China

<p><b>Objective:</b> To investigate the association between type 2 diabetes (T2D) and the risk of overall cancer and site-specific cancers in a Chinese population.</p> <p><b>Research design and methods:</b> Tianjin Urban Employee Basic Medical Insurance database (2003–2014) was used to identify patients with newly onset T2D in 2009, patients with prevalent T2D prior to 2009, and general individuals without T2D. Overall and site-specific cancer incidence rates and incidence rate ratios relative to general population were calculated for both incident and prevalent T2D cohorts. Multivariate Cox proportional hazards models adjusting for baseline characteristics and potential bias were conducted. Subgroup analyses based on gender and age were further conducted.</p> <p><b>Results:</b> For the year 2009, 21,208 patients with onset T2D (mean age 58.8 years; 48.1% female), 28,248 patients with prevalent T2D (mean age 63.7 years; 50.2% female) and 744,339 general individuals (mean age 43.2 years; 47.7% female) were identified. Controlling for confounders, diabetic patients had an overall 56%–59% higher risk of developing cancer, among which the highest risks by site were liver (adjusted hazard ratio [aHR] = 1.80–2.48), colorectal (aHR = 2.41–2.69) and stomach (aHR = 2.02–2.51) cancers (all <i>p</i> < .05). Patients with prevalent T2D had increased cancer risk in the pancreas (aHR = 4.52, <i>p</i> < .001). Female diabetic patients had increased risk in the kidneys (aHR = 3.22–3.31, <i>p</i> < .01). Patients aged between 50 and 59 years had the highest relative risk (90% higher), while the relative risk was the lowest among patients ≥70 (45% higher).</p> <p><b>Conclusion:</b> Type 2 diabetes was associated with increased overall cancer risk led by liver, colorectal and stomach cancers. Patients with longer diabetes duration were associated with higher pancreatic cancer risk and female diabetic patients had a higher risk of kidney cancer.</p

The difference-in-difference regression model of household CHE (n = 108).

<p>R² = 0.199; F = 5.089; p = 0.000.</p

Household characteristic of the two groups.

a<p>The household head (HH) may participate in more than one insurance system.</p>**<p>Significance at 5%.</p>***<p>Significance at 1%.</p><p>Compare the intervention group and control group in baseline survey.</p

Average proportion of CHE before and after NCMS reimbursement policies.

<p>Average proportion of CHE before and after NCMS reimbursement policies.</p

The flowchart of this study.

<p>This figure shows the study design of the study. N is the number of CHCs, and n is the number of staff in selected CHCs. In baseline survey, 480 questionnaires were distributed, and we finally got 447 valid questionnaires returned by eligible respondents. And then, 10 centers were randomly selected as the intervention group. The numbers of involved intervention centers and staff in each activity are shown in the figure. 390 staff participated in the follow-up survey, and the numbers of lost to follow-up and new enrollment are also shown. Other reasons for lost to follow-up included retirement, turnover, sick leave, causal leave, refusing to fill in the follow-up questionnaires, and uncompleted follow-up WSC answers. Finally, the facility-level intervention effects were evaluated based on all baseline and follow-up samples (n = 336+468 = 804) except Weibei respondents (n = 33).</p

Baseline characteristics comparison between the intervention and control CHCs.

<p>Baseline characteristics comparison between the intervention and control CHCs.</p

Effects of a Randomized Intervention to Improve Workplace Social Capital in Community Health Centers in China

<div><p>Objective</p><p>To examine whether workplace social capital improved after implementing a workplace social capital intervention in community health centers in China.</p><p>Methods</p><p>This study was conducted in 20 community health centers of similar size in Jinan of China during 2012–2013. Using the stratified site randomization, 10 centers were randomized into the intervention group; one center was excluded due to leadership change in final analyses. The baseline survey including 447 staff (response rate: 93.1%) was conducted in 2012, and followed by a six-month workplace social capital intervention, including team building courses for directors of community health centers, voluntarily public services, group psychological consultation, and outdoor training. The follow-up survey in July 2013 was responded to by 390 staff members (response rate: 86.9%). Workplace social capital was assessed with the translated and culturally adapted scale, divided into vertical and horizontal dimensions. The facility-level intervention effects were based on all baseline (n = 427) and follow-up (n = 377) respondents, except for Weibei respondents. We conducted a bivariate Difference-in-Difference analysis to estimate the facility-level intervention effects.</p><p>Results</p><p>No statistically significant intervention effects were observed at the center level; the intervention increased the facility-level workplace social capital, and its horizontal and vertical dimensions by 1.0 (p = 0.24), 0.4 (p = 0.46) and 0.8 (p = 0.16), respectively.</p><p>Conclusions</p><p>The comprehensive intervention seemed to slightly improve workplace social capital in community health centers of urban China at the center level. High attrition rate limits any causal interpretation of the results. Further studies are warranted to test these findings.</p></div

The distribution comparison of individual-level WSC total score.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114924#pone-0114924-g002" target="_blank">Fig. 2</a> shows the distributions of individual-level WSC total score. The histograms and fitting normal distribution curves in the upper-left and lower-left corners in the figure represent the observation frequencies and distributions before and after the intervention in the control group. The histograms and fitting normal distribution curves in the upper-right and lower-right corners in the figure represent the observation frequencies and distributions before and after the intervention in the intervention group.</p

The distribution comparison of individual-level vertical WSC score.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114924#pone-0114924-g004" target="_blank">Fig. 4</a> shows the distributions of individual-level vertical WSC score. The histograms and fitting normal distribution curves in the upper-left and lower-left corners in the figure represent the observation frequencies and distributions before and after the intervention in the control group. The histograms and fitting normal distribution curves in the upper-right and lower-right corners in the figure represent the observation frequencies and distributions before and after the intervention in the intervention group.</p

Baseline characteristics of the remaining participants, and those lost to follow-up.

<p>Baseline characteristics of the remaining participants, and those lost to follow-up.</p