Interactions among the sustainable development goals …and why they are important

The UN Sustainable Development Goals (SDGs) are a comprehensive, internationally agreed-upon set of objectives aiming to vastly improve economic, social and planetary well-being. How exactly to achieve these goals is now a point of discussion at many fora around the world. At one such forum, a Wilton Park Roundtable, an international group of stakeholders and experts found the efficiency of implementation to be a central issue. This efficiency in turn is related to the fact that the goals are all interconnected: In some cases steps towards achieving one goal may hinder the achievement of one or more other goals, leading to unintended “trade-offs”, or inefficiencies in implementation. But at least as often, actions towards a particular goal can have a positive influence on other goals, setting up beneficial “synergies” among the SDGs. Actions that take advantage of these synergies are key to implementing them efficiently because many different goals can be achieved at the same time and fewer resources are needed to achieve the whole set of goals. Saving resources would be a major payoff to countries confronted with the high costs of implementing the SDGs. The challenge now is to sort through the large number of possible interactions among SDGs to uncover and exploit the most important synergies while minimising the effects of trade-offs. Much can be done to achieve this at all levels, from local to global, including raising awareness about SDG interactions, reorienting investments, and reforming governance

Implementation of Antiretroviral Therapy for Life in Pregnant/Breastfeeding HIV+ Women (Option B+) Alongside Rollout and Changing Guidelines for ART Initiation in Rural Zimbabwe: The Lablite Project Experience.

BACKGROUND: Lifelong antiretroviral therapy (ART) for pregnant and breastfeeding women (Option B+) was rolled out in Zimbabwe from 2014, with simultaneous raising of the CD4 treatment threshold to 500 cells per cubic millimeter in nonpregnant/breastfeeding adults and children 5 years and over. METHODS: Lablite is an implementation project in Zimbabwe, Malawi, and Uganda evaluating ART rollout. Routine patient-level data were collected for 6 months before and 12 months after Option B+ rollout at a district hospital and 3 primary care facilities in Zimbabwe (2 with outreach ART and 1 with no ART provision before Option B+). RESULTS: Between September 2013 and February 2015, there were 1686 ART initiations in the 4 facilities: 91% adults and 9% children younger than 15 years. In the 3 facilities with established ART, initiations rose from 300 during 6 months before Option B+ to 869 (2.9-fold) and 463 (1.5-fold), respectively, 0-6 months and 6-12 months after Option B+. Post-Option B+, an estimated 43% of pregnant/breastfeeding women needed ART for their own health, based on World Health Organization stage 3/4 or CD4 ≤350 per cubic millimeter (64% for CD4 ≤500). Seventy-four men (22%) and 123 nonpregnant/breastfeeding women (34%) initiated ART with CD4 >350 after the CD4 threshold increase. Estimated 12-month retention on ART was 79% (69%-87%) in Option B+ women (significantly lower in younger women, P = 0.01) versus 93% (91%-95%) in other adults (difference P < 0.001). CONCLUSIONS: There were increased ART initiations in all patient groups after implementation of World Health Organization 2013 guidelines. Retention of Option B+ women was poorer than retention of other adults; younger women require attention because they are more likely to disengage from care

Health service needs and perspectives of remote forest communities in Papua New Guinea: study protocol for combined clinical and rapid anthropological assessments with parallel treatment of urgent cases

Introduction Our project follows community requests for health service incorporation into conservation collaborations in the rainforests of Papua New Guinea (PNG). This protocol is for health needs assessments, our first step in coplanning medical provision in communities with no existing health data. Methods and analysis The study includes clinical assessments and rapid anthropological assessment procedures (RAP) exploring the health needs and perspectives of partner communities in two areas, conducted over 6 weeks fieldwork. First, in Wanang village (population c.200), which is set in lowland rainforest. Second, in six communities (population c.3000) along an altitudinal transect up the highest mountain in PNG, Mount Wilhelm. Individual primary care assessments incorporate physical examinations and questioning (providing qualitative and quantitative data) while RAP includes focus groups, interviews and field observations (providing qualitative data). Given absence of in-community primary care, treatments are offered alongside research activity but will not form part of the study. Data are collected by a research fellow, primary care clinician and two PNG research technicians. After quantitative and qualitative analyses, we will report: ethnoclassifications of disease, causes, symptoms and perceived appropriate treatment; community rankings of disease importance and service needs; attitudes regarding health service provision; disease burdens and associations with altitudinal-related variables and cultural practices. To aid wider use study tools are in online supplemental file, and paper and ODK versions are available free from the corresponding author. Ethics and dissemination Challenges include supporting informed consent in communities with low literacy and diverse cultures, moral duties to provide treatment alongside research in medically underserved areas while minimising risks of therapeutic misconception and inappropriate inducement, and PNG research capacity building. Brighton and Sussex Medical School (UK), PNG Institute of Medical Research and PNG Medical Research Advisory Committee have approved the study. Dissemination will be via journals, village meetings and plain language summaries

Bayesian methods for instrumental variable analysis with genetic instruments (‘Mendelian randomization’): example with urate transporter SLC2A9 as an instrumental variable for effect of urate levels on metabolic syndrome

The ‘Mendelian randomization’ approach uses genotype as an instrumental variable to distinguish between causal and non-causal explanations of biomarker–disease associations. Classical methods for instrumental variable analysis are limited to linear or probit models without latent variables or missing data, rely on asymptotic approximations that are not valid for weak instruments and focus on estimation rather than hypothesis testing. We describe a Bayesian approach that overcomes these limitations, using the JAGS program to compute the log-likelihood ratio (lod score) between causal and non-causal explanations of a biomarker–disease association. To demonstrate the approach, we examined the relationship of plasma urate levels to metabolic syndrome in the ORCADES study of a Scottish population isolate, using genotype at six single-nucleotide polymorphisms in the urate transporter gene SLC2A9 as an instrumental variable. In models that allow for intra-individual variability in urate levels, the lod score favouring a non-causal over a causal explanation was 2.34. In models that do not allow for intra-individual variability, the weight of evidence against a causal explanation was weaker (lod score 1.38). We demonstrate the ability to test one of the key assumptions of instrumental variable analysis—that the effects of the instrument on outcome are mediated only through the intermediate variable—by constructing a test for residual effects of genotype on outcome, similar to the tests of ‘overidentifying restrictions’ developed for classical instrumental variable analysis. The Bayesian approach described here is flexible enough to deal with any instrumental variable problem, and does not rely on asymptotic approximations that may not be valid for weak instruments. The approach can easily be extended to combine information from different study designs. Statistical power calculations show that instrumental variable analysis with genetic instruments will typically require combining information from moderately large cohort and cross-sectional studies of biomarkers with information from very large genetic case–control studies

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Relationships of low serum vitamin D3 with anthropometry and markers of the metabolic syndrome and diabetes in overweight and obesity

Low serum 25 hydroxyvitamin D3 (vitamin D3) is known to perturb cellular function in many tissues, including the endocrine pancreas, which are involved in obesity and type II diabetes mellitus (TIIDM). Vitamin D3 insufficiency has been linked to obesity, whether obesity is assessed by body mass index (BMI) or waist circumference (waist). Central obesity, using waist as the surrogate, is associated with the metabolic syndrome (MetSyn), insulin resistance, TIIDM and atherosclerotic cardiovascular disease (CVD). We tested how vitamin D3 was related to measures of fat mass, MetSyn markers, haemoglobin A1c (HbA1c) and MetSyn in a cross-sectional sample of 250 overweight and obese adults of different ethnicities. There were modest inverse associations of vitamin D3 with body weight (weight) (r = -0.21, p = 0.0009), BMI (r = -0.18, p = 0.005), waist (r = -0.14, p = 0.03), [but not body fat % (r = -0.08, p = 0.24)], and HbA1c (r = -0.16, p = 0.01). Multivariable regression carried out separately for BMI and waist showed a decrease of 0.74 nmol/L (p = 0.002) in vitamin D3 per 1 kg/m2 increase in BMI and a decrease of 0.29 nmol/L (p = 0.01) per 1 cm increase in waist, with each explaining approximately 3% of the variation in vitamin D3 over and above gender, age, ethnicity and season

Predicting change in quality of life from age 79 to 90 in the Lothian Birth Cohort 1921

Purpose: Quality of life (QoL) decreases in very old age, and is strongly related to health outcomes and mortality. Understanding the predictors of QoL and change in QoL amongst the oldest old may suggest potential targets for intervention. This study investigated change in QoL from age 79 to 90 years in a group of older adults in Scotland, and identified potential predictors of that change. Method: Participants were members of the Lothian Birth Cohort 1921 who attended clinic visits at age 79 (n = 554) and 90 (n = 129). Measures at both time points included QoL (WHOQOL-BREF: four domains and two single items), anxiety and depression, objective health, functional ability, self-rated health, loneliness, and personality. Results: Mean QoL declined from age 79 to 90. Participants returning at 90 had scored significantly higher at 79 on most QoL measures, and exhibited better objective health and functional ability, and lower anxiety and depression than non-returners. Hierarchical multiple regression models accounted for 20.3–56.3% of the variance in QoL at age 90. Baseline QoL was the strongest predictor of domain scores (20.3–35.6% variance explained), suggesting that individual differences in QoL judgements remain largely stable. Additional predictors varied by the QoL domain and included self-rated health, loneliness, and functional and mood decline between age 79 and 90 years. Conclusions: This study has identified potential targets for interventions to improve QoL in the oldest old. Further research should address causal pathways between QoL and functional and mood decline, perceived health and loneliness

Recorded Mental Health Recovery Narratives as a Resource for People Affected by Mental Health Problems: Development of the Narrative Experiences Online (NEON) Intervention.

BACKGROUND: The internet enables sharing of narratives about health concerns on a substantial scale, and some digital health narratives have been integrated into digital health interventions. Narratives describing recovery from health problems are a focus of research, including those presented in recorded (eg, invariant) form. No clinical trial has been conducted on a web-based intervention providing access to a collection of Recorded Recovery Narratives (RRNs). OBJECTIVE: This study presents knowledge produced through the development of the Narrative Experiences Online (NEON) Intervention, a web-based intervention incorporating the algorithmic recommendation of RRNs. METHODS: Knowledge was gathered through knowledge integration (KI) activities. KI1 synthesized previous studies to produce the NEON Impact Model describing how accessing RRNs produces health-related outcomes. KI2 developed curation principles for the NEON Collection of RRNs through consultation with the NEON Lived Experience Advisory Panel and the curation of a preliminary collection. KI3 identified harm minimization strategies for the NEON Intervention through consultation with the NEON International Advisory Board and Lived Experience Advisory Panel. The NEON Intervention was finalized through 2 research studies (RS). In RS1, mental health service users (N=40) rated the immediate impact of randomly presented narratives to validate narrative feedback questions used to inform the recommendation algorithm. In RS2, mental health service users (n=25) were interviewed about their immediate response to a prototype of the NEON Intervention and trial procedures and then were interviewed again after 1 month of use. The usability and acceptability of the prototype and trial procedures were evaluated and refinements were made. RESULTS: KI1 produced the NEON Impact Model, which identifies moderators (recipient and context), mechanisms of connection (reflection, comparison, learning, and empathy), processes (identification of change from narrative structure or content and internalization of observed change), and outcomes (helpful and unhelpful). KI2 identified 22 curation principles, including a mission to build a large, heterogeneous collection to maximize opportunities for connection. KI3 identified seven harm minimization strategies, including content warnings, proactive and reactive blocking of narratives, and providing resources for the self-management of emotional distress. RS1 found variation in the impact of narratives on different participants, indicating that participant-level feedback on individual narratives is needed to inform a recommender system. The order of presentation did not predict narrative feedback. RS2 identified amendments to web-based trial procedures and the NEON Intervention. Participants accessed some narratives multiple times, use reduced over the 4-week period, and narrative feedback was provided for 31.8% (105/330) of narrative accesses. CONCLUSIONS: RRNs can be integrated into web-based interventions. Evaluating the NEON Intervention in a clinical trial is feasible. The mixed methods design for developing the NEON Intervention can guide its extension to other clinical populations, the design of other web-based mental health interventions, and the development of narrative-based interventions in mental health

Diabetes-Specific Nutrition Algorithm: A Transcultural Program to Optimize Diabetes and Prediabetes Care

Type 2 diabetes (T2D) and prediabetes have a major global impact through high disease prevalence, significant downstream pathophysiologic effects, and enormous financial liabilities. To mitigate this disease burden, interventions of proven effectiveness must be used. Evidence shows that nutrition therapy improves glycemic control and reduces the risks of diabetes and its complications. Accordingly, diabetes-specific nutrition therapy should be incorporated into comprehensive patient management programs. Evidence-based recommendations for healthy lifestyles that include healthy eating can be found in clinical practice guidelines (CPGs) from professional medical organizations. To enable broad implementation of these guidelines, recommendations must be reconstructed to account for cultural differences in lifestyle, food availability, and genetic factors. To begin, published CPGs and relevant medical literature were reviewed and evidence ratings applied according to established protocols for guidelines. From this information, an algorithm for the nutritional management of people with T2D and prediabetes was created. Subsequently, algorithm nodes were populated with transcultural attributes to guide decisions. The resultant transcultural diabetes-specific nutrition algorithm (tDNA) was simplified and optimized for global implementation and validation according to current standards for CPG development and cultural adaptation. Thus, the tDNA is a tool to facilitate the delivery of nutrition therapy to patients with T2D and prediabetes in a variety of cultures and geographic locations. It is anticipated that this novel approach can reduce the burden of diabetes, improve quality of life, and save lives. The specific Southeast Asian and Asian Indian tDNA versions can be found in companion articles in this issue of Current Diabetes Reports