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Primary Prevention of Gestational Diabetes Mellitus and Large-for-Gestational-Age Newborns by Lifestyle Counseling: A Cluster-Randomized Controlled Trial
Riitta Luoto ,
* E-mail: riitta.luoto@uta.fi
Affiliations UKK Institute for Health Promotion Research, Tampere, Finland, National Institute for Health and Welfare, Helsinki, Finland
Tarja I. Kinnunen,
Affiliation School of Health Sciences, University of Tampere, Finland
Minna Aittasalo,
Affiliation UKK Institute for Health Promotion Research, Tampere, Finland
Päivi Kolu,
Jani Raitanen,
Affiliations UKK Institute for Health Promotion Research, Tampere, Finland, School of Health Sciences, University of Tampere, Finland
Katriina Ojala,
Kirsi Mansikkamäki,
Satu Lamberg,
Tommi Vasankari,
Tanja Komulainen,
Sirkku Tulokas
Affiliation Tampere University Central Hospital, Tampere, Finland
Riitta Luoto,
Tanja Komulainen
https://doi.org/10.1371/journal.pmed.1001036
Riitta Luoto Tarja I. Kinnunen ... Sirkku Tulokas
Our objective was to examine whether gestational diabetes mellitus (GDM) or newborns' high birthweight can be prevented by lifestyle counseling in pregnant women at high risk of GDM.
Method and Findings
We conducted a cluster-randomized trial, the NELLI study, in 14 municipalities in Finland, where 2,271 women were screened by oral glucose tolerance test (OGTT) at 8–12 wk gestation. Euglycemic (n = 399) women with at least one GDM risk factor (body mass index [BMI] ≥25 kg/m2, glucose intolerance or newborn's macrosomia (≥4,500 g) in any earlier pregnancy, family history of diabetes, age ≥40 y) were included. The intervention included individual intensified counseling on physical activity and diet and weight gain at five antenatal visits. Primary outcomes were incidence of GDM as assessed by OGTT (maternal outcome) and newborns' birthweight adjusted for gestational age (neonatal outcome). Secondary outcomes were maternal weight gain and the need for insulin treatment during pregnancy. Adherence to the intervention was evaluated on the basis of changes in physical activity (weekly metabolic equivalent task (MET) minutes) and diet (intake of total fat, saturated and polyunsaturated fatty acids, saccharose, and fiber). Multilevel analyses took into account cluster, maternity clinic, and nurse level influences in addition to age, education, parity, and prepregnancy BMI. 15.8% (34/216) of women in the intervention group and 12.4% (22/179) in the usual care group developed GDM (absolute effect size 1.36, 95% confidence interval [CI] 0.71–2.62, p = 0.36). Neonatal birthweight was lower in the intervention than in the usual care group (absolute effect size −133 g, 95% CI −231 to −35, p = 0.008) as was proportion of large-for-gestational-age (LGA) newborns (26/216, 12.1% versus 34/179, 19.7%, p = 0.042). Women in the intervention group increased their intake of dietary fiber (adjusted coefficient 1.83, 95% CI 0.30–3.25, p = 0.023) and polyunsaturated fatty acids (adjusted coefficient 0.37, 95% CI 0.16–0.57, p<0.001), decreased their intake of saturated fatty acids (adjusted coefficient −0.63, 95% CI −1.12 to −0.15, p = 0.01) and intake of saccharose (adjusted coefficient −0.83, 95% CI −1.55 to −0.11, p = 0.023), and had a tendency to a smaller decrease in MET minutes/week for at least moderate intensity activity (adjusted coefficient 91, 95% CI −37 to 219, p = 0.17) than women in the usual care group. In subgroup analysis, adherent women in the intervention group (n = 55/229) had decreased risk of GDM (27.3% versus 33.0%, p = 0.43) and LGA newborns (7.3% versus 19.5%, p = 0.03) compared to women in the usual care group.
The intervention was effective in controlling birthweight of the newborns, but failed to have an effect on maternal GDM.
Current Controlled Trials ISRCTN33885819
Please see later in the article for the Editors' Summary
Citation: Luoto R, Kinnunen TI, Aittasalo M, Kolu P, Raitanen J, Ojala K, et al. (2011) Primary Prevention of Gestational Diabetes Mellitus and Large-for-Gestational-Age Newborns by Lifestyle Counseling: A Cluster-Randomized Controlled Trial. PLoS Med 8(5): e1001036. https://doi.org/10.1371/journal.pmed.1001036
Academic Editor: David Ludwig, Harvard Medical School, United States of America
Received: September 28, 2010; Accepted: April 7, 2011; Published: May 17, 2011
Copyright: © 2011 Luoto et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The main sources of funding in this study are (Finnish) Diabetes research fund, Competitive research funding from Pirkanmaa hospital district, Academy of Finland, Ministry of Education and Ministry of Social Affairs and Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Abbreviations: BMI, body mass index; CI, confidence interval; GDM, gestational diabetes mellitus; LGA, large for gestational age; OGTT, oral glucose tolerance test; SD, standard deviation; SGA, small for gestational age
Editors' Summary
Gestational diabetes mellitus (GDM) is diabetes that is first diagnosed during pregnancy. Like other types of diabetes, it is characterized by high levels of sugar (glucose) in the blood. Blood-sugar levels are normally controlled by insulin, a hormone that the pancreas releases when blood-sugar levels rise after meals. Hormonal changes during pregnancy and the baby's growth demands increase a pregnant woman's insulin needs and, if her pancreas cannot make enough insulin, GDM develops. Risk factors for GDM, which occurs in 2%–14% of pregnant women, include a high body-mass index (a measure of body fat), excessive weight gain or low physical activity during pregnancy, high dietary intake of polyunsaturated fats, glucose intolerance (an indicator of diabetes) or the birth of a large baby in a previous pregnancy, and a family history of diabetes. GDM is associated with an increased rate of cesarean sections, induced deliveries, birth complications, and large-for-gestational-age (LGA) babies (gestation is the time during which the baby develops within the mother). GDM, which can often be controlled by diet and exercise, usually disappears after pregnancy but increases a woman's subsequent risk of developing diabetes.
Why Was This Study Done?
Although lifestyle changes can be used to control GDM, it is not known whether similar changes can prevent GDM developing ("primary prevention"). In this cluster-randomized controlled trial, the researchers investigate whether individual intensified counseling on physical activity, diet, and weight gain integrated into routine maternity care visits can prevent the development of GDM and the occurrence of LGA babies among newborns. In a cluster-randomized controlled trial, groups of patients rather than individual patients are randomly assigned to receive alternative interventions, and the outcomes in different "clusters" are compared. In this trial, each cluster is a municipality in the Pirkanmaa region of Finland.
What Did the Researchers Do and Find?
The researchers enrolled 399 women, each of whom had a normal blood glucose level at 8–12 weeks gestation but at least one risk factor for GDM. Women in the intervention municipalities received intensified counseling on physical activity at 8–12 weeks' gestation, dietary counseling at 16–18 weeks' gestation, and further physical activity and dietary counseling at each subsequent antenatal visits. Women in the control municipalities received some dietary but little physical activity counseling as part of their usual care. 23.3% and 20.2% of women in the intervention and usual care groups, respectively, developed GDM, a nonstatistically significant difference (that is, a difference that could have occurred by chance). However, the average birthweight and the proportion of LGA babies were both significantly lower in the intervention group than in the usual care group. Food frequency questionnaires completed by the women indicated that, on average, those in the intervention group increased their intake of dietary fiber and polyunsaturated fatty acids and decreased their intake of saturated fatty acids and sucrose as instructed during counseling, The amount of moderate physical activity also tended to decrease less as pregnancy proceeded in the intervention group than in usual care group. Finally, compared to the usual care group, significantly fewer of the 24% of women in the intervention group who actually met dietary and physical activity targets ("adherent" women) developed GDM.
These findings indicate that intensified counseling on diet and physical activity is effective in controlling the birthweight of babies born to women at risk of developing GDM and encourages at least some of them to alter their lifestyle. However, the findings fail to show that the intervention reduces the risk of GDM because of the limited power of the study. The power of a study—the probability that it will achieve a statistically significant result—depends on the study's size and on the likely effect size of the intervention. Before starting this study, the researchers calculated that they would need 420 participants to see a statistically significant difference between the groups if their intervention reduced GDM incidence by 40%. This estimated effect size was probably optimistic and therefore the study lacked power. Nevertheless, the analyses performed among adherent women suggest that lifestyle changes might be a way to prevent GDM and so larger studies should now be undertaken to test this potential primary prevention intervention.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001036.
The US National Institute of Diabetes and Digestive and Kidney Diseases provides information for patients on diabetes and on gestational diabetes (in English and Spanish)
The UK National Health Service Choices website also provides information for patients on diabetes and on gestational diabetes, including links to other useful resources
The MedlinePlus Encyclopedia has pages on diabetes and on gestational diabetes; MedlinePlus provides links to additional resources on diabetes and on gestational diabetes (in English and Spanish)
More information on this trial of primary prevention of GDM is available
Gestational diabetes mellitus (GDM) is defined as a type of diabetes first diagnosed during pregnancy [1]. Incidence of GDM varies from 2% to 14% globally and it is increasing [2]. Maternal glucose has been associated with a risk of adverse pregnancy outcomes in a linear manner [3]. Borderline GDM has been linked with higher rates of cesarean sections and induced deliveries, shoulder dystocia and birth injuries [4], and pathogenesis in the offspring of overweight and metabolic syndrome [5].
High intake of saturated fat, low intake of polyunsaturated fat, and excessive gestational weight gain may increase the risk of GDM [6]–[10]. Physical activity is also associated with decreased risk of GDM [11]. Lifestyle modifications have been shown to be a valuable adjunctive therapy of GDM [12] but to date there are no adequately powered trials on primary prevention of GDM. Earlier studies on prevention of gestational weight gain by dietary and physical activity counseling have found favorable results [13] and structured aerobic exercise training has been shown to decrease birthweight of the newborns [14]. In our own pilot study, intensive lifestyle counseling produced favorable changes both in diet and physical activity [15],[16]. The aim of this cluster-randomized trial was to examine whether individual intensified counseling on physical activity, diet, and weight gain integrated into routine maternity care visits could prevent the development of GDM and newborns' high birthweight adjusted for gestational age.
Design and Study Population
The methods of this study have been described in detail previously (Text S1 and S2) [17]. The study is a cluster-randomized trial conducted in maternity clinics of primary health care centers of 14 municipalities in Pirkanmaa region in south-western Finland. All 14 municipalities with at least 70 annual deliveries were recruited to the study. The unit of randomization was municipality. In the randomization process, participating municipalities were first pairwise matched with regard to annual number of births, size and socio-economic level of the population, estimated incidence of GDM, and urbanity level. Municipalities were then randomized by computer. The rationale for using cluster randomization was to avoid contamination between trial arms, which would have occurred if individuals or clinics were randomized. All 53 nurses working in maternity clinics in these municipalities recruited pregnant women at 8–12 wk gestation between 1 October 2007 and 31 December 2008. The study was completed at the end of 2009, when all participating women had given birth.
Pregnant women were eligible to enter the study if they had at least one of the following risk factors: body mass index (BMI) ≥25 kg/m2 based on measured height and self-reported prepregnancy weight; GDM or any signs of glucose intolerance or newborn's macrosomia (≥4,500 g) in any earlier pregnancy; type 1 or 2 diabetes in first- or second-degree relatives; or age ≥40 y. Women were excluded if they had any of the following: at least one of the three baseline (8–12 wk gestation) oral glucose tolerance test (OGTT) measurements was abnormal (fasting blood glucose ≥5.3 mmol/l, >10.0 mmol/l at 1 h, and >8.6 mmol/l at 2 h) [1]; prepregnant type 1 or 2 diabetes; inability to speak Finnish; age <18 y; multiple pregnancy; physical restriction preventing physical activity; substance abuse; treatment or clinical history for psychiatric illness.
The research protocol was approved by the Urho Kekkosen Kuntoinstituuttisäätiö institute review board, the ethical committee of Pirkanmaa Hospital District, and the physicians in charge of primary health care in the 14 municipalities. All participants provided written informed consent.
The intervention continued from the first maternity clinic visit at 8–12 wk gestation until 37 wk gestation (Text S1) [17]. At the first visit the recommendations for gestational weight gain [18] were discussed and an appropriate weight gain graph was selected from the follow-up notebook to guide the participant in monitoring her weight gain. The primary physical activity counseling was implemented at 8–12 wk gestation and the primary dietary counseling session at 16–18 wk gestation. The rationale for implementing physical activity and dietary counseling at separate visits was 2-fold: the nurses' time for counseling was limited to 2 h in total for the first visit and thus only one primary counseling focus could be included. Secondly, the nurses were more familiar with dietary issues and, therefore, including physical activity counseling in the first visit emphasized the difference between usual care. Physical activity counseling was enhanced at four, and diet counseling at three subsequent visits. If OGTT was pathological at 26–28 wk gestation, women were additionally referred to other health care specialists.
Aims of the physical activity counseling were to increase leisure time physical activity of those pregnant women who were not fulfilling the physical activity recommendations to the recommended level for health [19] and to maintain or adjust leisure time physical activity of those women who were already fulfilling the recommendations. The minimum weekly leisure time physical activity dose, including also light-intensity physical activity, entered progressively in the plan was 800 MET (multiples of resting metabolic equivalents) minutes. This amount is in line with Haskell et al. [20], suggesting after the initiation of this study the maximum of 750 MET minutes of moderate-intensity physical activity for health. During the primary visit the participants were offered an opportunity to participate in monthly thematic meetings on physical activity including group exercise.
Evaluation of leisure-time physical activity was based on a validated self-report [21].
Based on Finnish dietary recommendations, the goal of dietary counseling was to help participants achieve a healthy diet containing ≤10% saturated fat, 5%–10% polyunsaturated fat, 25%–30% total fat, and <10% saccharose of total energy intake, and 25–35 g/d fiber [22]. A study that was successful in preventing type 2 diabetes mellitus in Finland was used as a reference [23]. In practice, the participants were advised (1) to consume vegetables, fruits, and berries, preferably at least five portions (400 g) a day; (2) to select mostly high fiber bread (>6 g fiber/100 g) and other whole-meal products; (3) to select mostly fat-free or low-fat versions of milk and milk products (e.g., yoghurt, cheese, ice cream) and of meat and meat products; (4) to eat fish at least twice per week (excluding the fish species not recommended for pregnant women); (5) to use moderate amounts of soft table spreads on bread, oil-based salad dressing in salad, and oil in cooking and baking; (6) to consume seldom and only in small-portions foods high in fat; and (7) to consume seldom and only in small-portions snacks containing high levels of sugar and/or fat (e.g., sweets, high-sugar drinks, cookies, ice cream, sweet and savoury pastries, potato chips) [24].
Counseling cards helped the nurses to standardize their counseling. The participants used follow-up notebooks to set their individual plans for physical activity and dietary changes and to a keep record of their adherence to their plans.
Women in the usual care group received no counseling beyond usual care, which includes some dietary counseling (partly on different topics) and follow-up of gestational weight [15], but only little physical activity counseling [16]. All nurses were supported with meetings every third month during the intervention.
Outcome Variables and Data Collection
The two primary outcomes of the trial were the proportion of women with GDM based on 26–28 gestation week OGTT (maternal outcome) and the newborns' birthweight adjusted for gestational age (neonatal outcome). Diagnosis of GDM was based on the OGTT (at least one of the following criteria was met: fasting blood glucose ≥5.3 mmol/l, >10.0 mmol/l at 1 h, and >8.6 mmol/l at 2 h) [1].
In addition to this definition, we also combined the birthweight of the newborn (≥4,500 g or >4,000 g) or possible use of insulin or other diabetic medication during pregnancy to two variations of GDM diagnosis, since the OGTT might have been pathological after 26–28 wk gestation. The rationale for using birthweight was that performing third OGTT measurement at 37–39 wk gestation was not feasible. The information on the outcomes was based both on hospital records and measurements made by the research group.
Level of glucose intolerance and insulin resistance was based on the homeostasis model assessment insulin resistance (HOMA-IR) calculator [25] and calculated as fasting insulin concentration (µU/ml) × fasting glucose concentration (mmol/l)/22.5. Blood samples for determination of glucose intolerance and insulin resistance were taken at 8–12 and 26–28 wk gestation.
Neonatal outcomes to be reported in this article are sex of the newborn, proportions of macrosomic (≥4,500 g) and large-for-gestational-age (LGA) and small-for-gestational-age (SGA) newborns, gestational age at delivery, birthweight standard deviation (SD) score, crown-heel length and crown-heel length SD score, ponderal index, and newborn head circumference. LGA refers to an infant whose birthweight is above the 90th percentile adjusted gestational age and SGA for an infant whose birthweight is below the 10th percentile adjusted gestational age. Birthweight percentiles and SD scores were based on Medical Birth Registry information on Finnish children born during years 2004–2006 and the method used by Kramer et al. [26]. Crown-heel length is the distance from the crown of the head to the heel and measured with a measuring board. Head circumference is measured with measuring tape and obtained to the nearest millimeter. Ponderal index was calculated as birthweight in kilograms divided by the cube of the crown-heel length in meters. Measurements for all neonatal outcomes were performed immediately after birth by the hospital midwifes and the information was gathered for the study from maternal records.
Other secondary outcomes were (1) gestational weight gain calculated on the basis of self-reported prepregnancy weight and the last measured weight during pregnancy in the maternal care, (2) the need for insulin or other diabetic medication from 26–28 wk gestation onwards, and (3) child weight development after delivery, which will be reported in a separate article. In this article we also report the proportion of women with pre-eclampsia determined as protein in the urine sample assessed by urine testing stick after 20 wk gestation and systolic blood pressure ≥140 mmHg and diastolic blood pressure ≥90 mmHg. All this information was obtained from maternal records. Additionally, data on physical activity and diet was collected by validated questionnaires at 8–12 (questions covering the 1-mo period before pregnancy), 26–28, and 36–37 wk gestation (Text S1) [17],[21],[24].
Evaluation of leisure-time physical activity was based on a validated self-report (21) at baseline, 26–28 wk gestation, and 36–37 wk gestation. At baseline, physical activity prior to pregnancy was inquired. At follow-ups, the questions concerned physical activity during the past 3 wk. The degree of breathlessness (strong, some, none) was used to help the women to determine the intensity of their physical activity. In quantifying MET minutes, 3 METs were used for light, 5 METs for moderate, and 7 METs for vigorous physical activity. In the analysis, moderate and vigorous MET minutes were summed to form MET minutes for at least moderate physical activity. Dietary habits were assessed by using a validated 181-item food frequency questionnaire [24] at baseline, 26–28 wk gestation, and 36–37 wk gestation. At baseline, the women were asked questions about their diet during 1 mo prior to the pregnancy, since their diet may have changed due to nausea or vomiting at the beginning of the pregnancy. In the follow-up, the women were asked questions about their diet during the previous month.
Behavior changes, expected to contribute to the possible effects of the intervention on the outcomes, were changes in leisure-time physical activity (weekly MET minutes) and diet (intake of total fat, saturated and polyunsaturated fatty acids, saccharose, and fiber).
Women were defined to be adherent to the recommendations, if they fulfilled at least four of the five dietary aims and/or their physical activity exceeded 800 MET minutes/wk at 36–37 wk gestation and their total weight gain did not exceed their BMI-specific limits.
The nurses elicited information on selected adverse effects [27] by a structured interview at four of the visits. Adverse effects included nausea, bleeding, painful contractions, dizziness, breathlessness, headache, chest pain, tiredness/fatigue, calf pain, or musculoskeletal problems. The response alternatives were "no," "sometimes," and "often."
The power calculations for this study were based on the assumption of detecting a 40% reduction in the incidence of GDM (GDM incidence 40% in the usual care municipalities and 24% in the intervention municipalities). With these incidences of GDM, the power of the study would be 0.80, significance level 0.05, and coefficient of variation of rate between clusters, indicating cluster sampling, 0.1. On the basis of these assumptions, 420 women were needed for the analyses. As we expected a drop-out rate similar to the one in our pilot study (25%), we needed to recruit a total of 560 women to the study.
Statistical analysis was performed by intention to treat approach in the originally assigned groups. Numbers and percentages are reported for categorical variables and means with standard deviations (SDs) or 95% confidence intervals (CIs) for continuous variables. Statistical analyses for adverse effects were performed using SPSS software (version 17.0.1) and adverse effect multilevel analyses by using STATA (version 11.0). The main method for between-group differences was multilevel analysis enabling simultaneous examination of cluster, clinic, nurse, and individual-level influences on outcomes and the correction of results for between-cluster, between-clinic, and between-nurse variation.
The effects of the intervention on maternal and neonatal outcomes and changes in physical activity and diet were analyzed by using STATA's generalized linear latent and mixed models (GLLAMM) and multilevel mixed-effects linear regression (xtmixed) by fitting four-level random effects models. Individual-level variables included as covariates in the multilevel models were age (continuous), education (low, basic or secondary education; medium, polytechnic; high, university degree), sex of the infant, parity (0 or ≥1), prepregnancy BMI (continuous), smoking (never, before pregnancy only, before and during pregnancy). Total gestational weight gain was not included in the multilevel model since it belongs to the causal pathway of the effect of lifestyle counseling. Gestational age in days was included in analyzing the abnormal OGTT at 26–28 wk gestation, because a higher proportion of women in the usual care group (21.4%) than in the intervention group (16.5%) underwent OGTT before 26 wk gestation. Four outliers were excluded from analyses: women with BMI 48.5 or 40.4 (two women in the intervention group) and women whose newborns birthweight were 740 g (one woman in the intervention group) or 850 g (one woman in the usual care group). However, including outliers to the analyses did not change the results. The incidence of GDM and LGA was also calculated by including only adherent women in the intervention group to the analyses and estimating the association by using chi-square statistics.
Of the 2,271 women screened, 520 (22.9%) in the intervention group and 496 (21.8%) in the control group were preliminarily eligible for the study. Of them, 343 (66.0%) in the intervention and 297 (59.9%) in the usual care group agreed to participate in the trial (Figure 1). However, 81 (23.6%) of the participants in intervention group and 93 (31.3%) of the participants in the usual care group had an abnormal OGTT result at baseline (8 to 12 wk gestation) and were thus excluded. The final number of participants in the analyses was 219 (89.0% of participants receiving allocated intervention) in the intervention group and 180 (91.8% of participants receiving allocated intervention) in the usual care group. The intervention and the usual care group had an equal proportion of women fulfilling one (68.5% versus 66.5%), two (28.3% versus 27.9%), or three of the inclusion criteria (2.7% versus 4.5%).
Figure 1. CONSORT flow diagram of the cluster-randomized trial.
https://doi.org/10.1371/journal.pmed.1001036.g001
The mean age of the women was 30 y and 47% of them were primiparous in the intervention and 41% in the usual care group (Tables 1 and S1). Average BMI before pregnancy was 26 kg/m2 in both groups. There were more women in the intervention group (26.8%) with high education than in the usual care group (20.6%). Being overweight or having a family history of diabetes were the most common reasons for inclusion (Table S1).
Table 1. Baseline characteristics of the study population.
https://doi.org/10.1371/journal.pmed.1001036.t001
There were no significant differences between the intervention and the usual care group at baseline or at 26–28 wk gestation in glucose intolerance measurements (Table 2). The proportion of women with GDM based on different criteria did not differ between the groups (Table 3). Total gestational weight gain, pre-eclampsia, or use of diabetic medication did not differ significantly between the groups (Table 3).
Table 2. Means and SD for variables related to the OGTT, insulin, and homeostatic model insulin resistance at 8–12 and 26–28 wk gestation.
Table 3. Maternal and neonatal outcomes of the trial.
Among the newborns, the proportion of males was 54.0% in the intervention and 43.1% in the usual care group. Gestational age at delivery was similar in both groups (39.4±1.9 wk versus 39.6±1.3 wk). The average newborns' birthweight was lower in the intervention group than in the usual care group (3,532 g versus 3,659 g, adjusted p = 0.035) (Table 3). Between-group differences in birthweight (absolute effect size −133 g, 95% CI −231 to −35) and in birthweight per gestational age (absolute effect size −3.08, 95% CI −5.29 to −0.87) remained significant after taking cluster, clinic, nurse, maternal age, education, sex of the infant, parity, prepregnancy BMI, gestational weight gain, and smoking into account (p = 0.024). Birthweight SD score was not significantly different between groups. The intracluster correlation coefficient (ICC) for birthweight was 0.02, when adjusted for all covariates. Newborns' birthweight did not differ significantly between women with one or more inclusion criteria.
The proportion of LGA infants was lower in the intervention (12.1%) than in the usual care group (19.7%, p = 0.042) and the statistical significance persisted after adjusting for individual-level covariates (p = 0.043) (Table 3). There were no statistically significant differences between the groups in the proportion of macrosomic infants, crown-heel length, crown-heel length SD score, SGA, ponderal index, or head circumference. Since there were only four infants with low birthweight (<2,500 g), those results are not shown.
Women in the intervention group had a tendency to a smaller decrease in at least moderate activity MET minutes (adjusted coefficient 91, 95% CI −37 to 219, p = 0.17) than women in the usual care group from baseline to 26–28 wk gestation (Table 4). The intervention group reduced their intake of saturated fatty acids from baseline to 26–28 wk gestation as compared to the usual care group (adjusted coefficient −0.56, 95% CI −0.95 to −0.17, p = 0.005) and a similar, but statistically nonsignificant change was observed in total fat intake (Table 4). Intervention group also differed from usual care group in decreased use of saccharose (adjusted coefficient −0.59, 95% CI −1.16 to −0.03, p = 0.04) at 26–28 wk gestation. When comparing the between-group differences in changes from baseline to 36–37 wk gestation, the intervention group had reduced their intake of saturated fatty acids (coefficient −0.63, 95% CI −1.12 to −0.15, p = 0.01) and saccharose (adjusted coefficient −0.83, 95% CI −1.55 to −0.11, p = 0.023) and increased their intake of dietary fiber (coefficient 1.83, 95% CI 0.30–3.35, p = 0.019) and polyunsaturated fatty acids (coefficient 0.37, 95% CI 0.16–0.57, p<0.001).
Table 4. Physical activity and dietary changes from baseline to 26–28 and 36–37 wk gestation in the intervention and the usual care groups.
Incidence of the Primary Outcomes in Adherent Women
The adherent women in the intervention group had less GDM (27.3% [15/55] versus 33.0% [59/179], p = 0.43) and lower proportion of LGA newborns (7.3% [4/55] versus 19.5 [34/174], p = 0.03) when compared to all women in the usual care group (not shown in the table).
The intervention group did not statistically significantly differ in any of the selected adverse effects when maternal age and all covariates were taken into account, except in headache at 32–34 wk gestation (41.5% among intervention group versus 56.5% among usual care group, adjusted p = 0.019) (Table 5).
Table 5. Incidence of selected adverse effects (%) among intervention and usual care groups by gestation week.
Our study evaluated the effectiveness of lifestyle counseling in primary prevention of GDM among a group of euglycemic women with at least one risk factor of GDM. Using a cluster-randomized controlled design, lifestyle counseling was effective in controlling the proportion of LGA newborns, but the result concerning GDM was inconclusive. The intervention had beneficial effects on four of the five dietary aims, i.e., the intake of dietary fiber, saccharose, and saturated and polyunsaturated fatty acids. Additionally, a statistically nonsignificant tendency for lower decrease in at least moderate activity MET minutes by 26–28 wk gestation was observed among the intervention group as compared to the usual care group. Women adherent to the lifestyle aims had lower proportion of LGA newborns and a tendency to lower incidence of GDM.
Earlier studies related to GDM have studied, for example, thresholds for treatment [21],[22] or prevention of pregnancy-related weight gain, and reported some results related to GDM [13],. Landon and colleagues' [29] trial included women with mild GDM, and an Australian trial [30] women with definite GDM at 24–34 wk gestation. Both trials had composite outcomes including perinatal mortality and neonatal complications associated with maternal hyperglycemia [29],[30]. In our study the main outcomes were GDM and LGA newborns, both reflecting maternal hyperglycemia. Studies in which newborn birthweight has been a primary outcome have shown that treatment of maternal gestational hyperglycemia can be beneficial on newborns' birthweight [28]. In an observational hyperglycemia and adverse pregnancy outcomes (HAPO) study [3], maternal blood glucose levels were associated with LGA (birthweight above 90th percentile). In our study, no significant differences between the groups in neonatal ponderal index, total gestational weight gain, macrosomia, or head circumference was discovered. This finding may also be due to the fact that power calculations were based on the main outcome—incidence of GDM. The calculations were not based on earlier trials, since there were no similar studies available at the time of the initiation of the study. The proportion of women with GDM among the intervention group was expected to be half lower than in the usual care group according to the power calculations, but the results did not support reduction. Although the target sample size (n = 420) was almost met, the expected difference of 40% in the incidence of GDM between the groups was most likely too ambitious and thus the study lacked sufficient power on the GDM outcome. The proportion of excluded women with abnormal OGTT already at the 8–12 wk gestation was unexpectedly high (23.6% in the intervention group, 31.3% in the usual care group), which decreased our sample size. The recruitment process was 6 mo longer than initially planned, since pregnant women were reluctant to participate in the lifestyle modification program because of lack of time or other personal reasons.
GDM treatment trials have used different intervention strategies: use of insulin, self-monitoring of glucose, and dietary intervention [28]. Lifestyle counseling, in terms of physical activity, diet, and weight gain, has not been incorporated as an intervention strategy in GDM prevention or treatment in any adequately powered study. Physical activity is, however, known to have acute effects on blood glucose and insulin sensitivity during a GDM pregnancy [30], which may further lead to favorable effects on newborns' birthweight. Small studies with instructed exercise training and dietary advice have shown favorable trends on reducing excessive weight gain, GDM, and macrosomia, but only three trials using dietary advice in GDM prevention have been published [31]. In these trials, low-glycemic diet was related to an average of 446 g lighter babies, but the evidence is still inconclusive due to small sample sizes and diverse outcomes in the trials [31]. In our study, the changes observed in dietary outcomes especially by 36–37 wk gestation may at least partly explain the between-group difference observed in birthweight of the newborns. On the other hand, time from the initiation of the dietary counseling (16–18 wk gestation onwards) to the measurement of GDM at 26–28 wk gestation may have been too short to produce changes in dietary habits and further to have an effect on development of GDM. Changes in both physical activity and diet were fairly similar as published in our pilot trial [15],[16]. Adherence to the lifestyle aims is a significant issue when considering effect of the intervention on the primary outcomes. Our definition for adherence included achievement of at least four dietary aims and/or the physical activity aim and the weight gain recommendation. Our analyses on adherence suggest that achievement of the aims of all these three components of the intervention (rather than only part of them) is associated with a lower risk for LGA and may be associated with lower risk of GDM.
Another possible reason for negative result concerning GDM prevention may be the risk group status of the women recruited to the trial. Since we included women with at least one GDM risk factor, most women had quite low risk for developing GDM. If we had included women with high risk of GDM, e.g., obese women or women with previous insulin-treated GDM, the results might have been different.
Our study did not show an increase in the incidence of adverse events or preterm birth in the intervention group. Thus, lifestyle counseling implemented by the nurses may be considered safe. Our counseling procedure has been shown to be feasible [15],[16], and it may be more applicable in maternity health care than interventions delivered by research nurses or other staff. In a study with individual randomization, not only statistical power, but also risk for contamination between trial arms would have been higher than in our cluster-randomized trial. The generalizability of our findings is higher than efficacy trials due to implementation in real-world instead of laboratory settings, although limited to women with no abnormal findings in OGTT during 8–12 wk gestation.
Limitations of our study also include the absence of late pregnancy measurement of maternal glucose intolerance, and owing to this, we were not able to assess maternal endpoints close to delivery, and thus high birthweight was used as a marker of longstanding glucose intolerance during pregnancy. Inaccuracy in birthweight, crown-heel length, and head circumference measurements in hospital is likely to be nondifferential, since the possibility of such errors was equal in both groups. Secondly, the differences between groups might have been even larger if this inaccuracy had not existed. An inevitable limitation is also that the women and the nurses in the usual care group could not be blinded for the purpose of the study, which may have resulted in changes in their health behavior or counseling practices.
Evidence on the primary prevention of GDM and its consequences among women at risk but with normal glucose tolerance has been lacking. Our study has shown that lifestyle counseling is effective in decreasing newborns' birthweight among women at risk of GDM and producing behavioral change. We failed to find an effect on GDM diagnosed at 26–28 wk gestation or later, but the analyses performed among the adherent women suggest that favorable changes in behavior may decrease the risk of LGA offspring. Results from ongoing clinical trials [32],[33] may strengthen the evidence on the effectiveness of lifestyle modifications on maternal and fetal hyperglycemia and its consequences. The findings of our study emphasize counseling on the topics of physical activity, diet, and weight gain in maternity care especially for women at risk for GDM in order to prevent LGA newborns possibly causing problems in delivery, and both the mother's and the child's later weight development.
Alternative Language Abstract S1.
French translation of the abstract.
https://doi.org/10.1371/journal.pmed.1001036.s001
(DOC)
Italian translation of the abstract.
Portuguese translation of the abstract.
Spanish translation of the abstract.
Table S1.
Inclusion criteria, pre-pregnancy BMI, education, smoking, parity and age by clusters in intervention and usual care areas.
Text S1.
Protocol (previously published in [17]).
CONSORT checklist.
Mikael Fogelhom, Academy of Finland, is acknowledged for his help in nutritional questions when planning the study. Päivi Viitanen, UKK Institute for Health Promotion, participated in data collection and coding throughout the process. Leena Hilakivi-Clarke, Georgetown University, Washington (D.C.), United States, contributed to the endocrinological issues in blood samples. Suvi Virtanen, National Institute for Health and Welfare, contributed to the dietary linkage of the study (FINELI). The following persons gave important advice during the project: Matti Pasanen, UKK Institute for Health Promotion (statistical questions and power calculations); Hannu Oja, University of Tampere (statistics); Matti Salo, Tampere University Central Hospital (pediatrics); Tiina Solakivi, University of Tampere (biochemistry); Ulla Hakala, Ulla Honkanen, Taru Helenius, Sirke Rasinperä, and Leena Aura from the UKK Institute laboratory participated in the data collection. Nurses and midwives from the following maternity centers are acknowledged for their participation to the implementation of the trial: Pirkkala, Ylöjärvi, Akaa (Toijala, Viiala, Kylmäkoski), Kangasala, Hämeenkyrö, Mänttä-Vilppula, Nokia, Virrat, Mouhijärvi (Sastamala), Lempäälä, Vesilahti, Orivesi, Valkeakoski, and Tampere (Muotiala).
Conceived and designed the experiments: RL TIK MA KO. Performed the experiments: KM KO TV. Analyzed the data: JR RL PK TK. Contributed reagents/materials/analysis tools: TV JR PK. Wrote the paper: RL PK TIK MA TV ST. ICMJE criteria for authorship: RL TIK MA KO PK JR SL TV KM TK ST. Results and conclusions: RL TIK MA KO PK JR SL TV KM TK ST. Enrolled patients: TIK MA RL. First draft: PK RL. Planning the counseling and preparing related material, training the nurses for counseling: TIK MA. Design of the thematic meetings on physical activity and material: MA. Group exercise design: KO.
1. (2010) Diagnosis and classification of diabetes mellitus. Diabetes Care 33: S62–S69.
2. Ferrara A (2007) Increasing prevalence of gestational diabetes mellitus: a public health perspective. Diabetes Care 30: S141–S146.
3. Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, et al. (2008) Hyperglycemia and adverse pregnancy outcomes. New Engl J Med 358: 1991–2002.
4. Ju H, Rumbold AR, Willson KJ, Crowther CA (2008) Borderline gestational diabetes mellitus and pregnancy outcomes. BMC Pregnancy and Childbirth 8: 31.
5. Clausen TD, Mathiesen ER, Hansen T, Pedersen O, Jensen DM, et al. (2009) Overweight and the metabolic syndrome in adult offspring of women with diet-treated gestational diabetes mellitus or type 1 diabetes. J Clin End Metab 94: 2464–2470.
6. Bo S, Menato G, Lezo A, Signorile A, Bardelli C, et al. (2001) Dietary fat and gestational hyperglycaemia. Diabetologia 44: 972–978.
7. Hedderson MM, Gunderson EP, Ferrara A (2010) Gestational weight gain and risk of gestational diabetes mellitus. Obstet Gynecol 115: 597–604.
8. Morisset A-S, St-Yves A, Veillette J, Weisnagel SJ, Tchernof A, et al. (2010) Prevention of gestational diabetes mellitus: a review of studies on weight management. Diabetes Metab Res Rev 26: 17–25.
9. Saldana TM, Siega-Riz AM, Adair LS (2004) Effect of macronutrient intake on the development of glucose intolerance during pregnancy. Am J Clin Nutr 79: 479–486.
10. Wang Y, Storlien LH, Jenkins AB, Tapsell LC, Jin Y, et al. (2000) Dietary variables and glucose tolerance in pregnancy. Diabetes Care 23: 460–464.
11. Tobias DK, Zhang C, van Dam RM, Bowers K, Hu FB (2011) Physical activity before and during pregnancy and risk of gestational diabetes mellitus: a meta-analysis. Diabetes Care 34: 223–229.
12. (2006) Impact of physical activity during pregnancy and postpartum on chronic disease risk. Med Sci Sports Exerc 38: 989–1006.
13. Streuling I, Beyerlein A, von Kries R (2010) Can gestational weight gain be modified by increasing physical activity and diet counselling? A meta-analysis of interventional trials. Am J Clin Nutr 92: 678–687.
14. Hopkins SA, Baldi JC, Cutfield WS, McCowan L, Hofman PL (2010) Exercise training in pregnancy reduces offspring size without changes in maternal insulin sensitivity. J Clin Endocr Metab 95: 2080–2088.
15. Kinnunen TI, Pasanen M, Aittasalo M, Fogelholm M, Hilakivi-Clarke L, et al. (2007) Preventing excessive weight gain during pregnancy - a controlled trial in primary health care. Eur J Clin Nutr 61: 884–891.
16. Aittasalo M, Pasanen M, Fogelholm M, Kinnunen TI, Ojala K, et al. (2008) Physical activity counseling in maternity and child health care - a controlled trial. BMC Women's Health 8: 14.
17. Luoto R, Kinnunen TI, Aittasalo M, Ojala K, Mansikkamäki K, et al. (2010) Prevention of gestational diabetes: design of a cluster-randomised controlled trial and one year- follow-up. BMC Pregnancy and Childbirth 10: 39.
18. Institute of Medicine (1990) Nutrition during pregnancy. Weight gain and nutrient supplements. Report of the Subcommittee on Nutritional Status and Weight Gain during Pregnancy. Subcommittee on Dietary Intake and Nutrient Supplements during Pregnancy. Committee on Nutritional Status during Pregnancy and Lactation. Food and Nutrition Board. Washington (D.C.): National Academy Press.
19. Artal R, O'Toole M (2003) Guidelines of the American College of Obstetricians and Gynecologists for exercise during pregnancy and the postpartum period. Br J Sports Med 37: 6–12.
20. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, et al. (2007) Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Circulation 116: 1081–93.
21. Aittasalo M, Pasanen M, Fogelholm M, Ojala K (2010) Validity and repeatability of a short pregnancy leisure time physical activity questionnaire. J Phys Act Health 7: 109–118.
22. Valtion ravitsemusneuvottelukunta. [Finnish dietary recommendations at 2005] Suomalaiset ravitsemussuositukset 2005 – ravinto ja liikunta tasapainoon (in Finnish). Helsinki: Edita .
23. Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, et al. (2001) Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. New Engl J Med 344: 1343–1350.
24. Erkkola M, Karppinen M, Javanainen J, Rasanen L, Knip M, et al. (2001) Validity and reproducibility of a food frequency questionnaire for pregnant Finnish women. Am J Epidemiol 154: 466–476.
25. Wallace TM, Levy JC, Matthews DR (2004) Use and abuse of HOMA modeling. Diab Care 27: 1487–1495.
26. Kramer MS, Platt RW, Wen SW, Joseph KS, Allen A, et al. (2001) A new and improved population-based Canadian reference for birth weight for gestational age. Pediatrics 108: E35.
27. ACOG Committee opinion (2002) Number 267. January 2002: exercise during pregnancy and the postpartum period. Obstet Gynecol 99: 171–173.
28. Horvath K, Koch K, Jeitler K, Matyas E, Bender R, et al. (2010) Effects of treatment in women with gestational diabetes mellitus: systematic review and meta-analysis. Br Med J 340: c1395.
29. Landon MB, Spong CY, Thom E, Carpenter MW, Ramin SM, et al. (2009) A multicenter, randomized trial of treatment for mild gestational diabetes. N Engl J Med 361: 1339–1348.
30. Crowther CA, Hiller JE, Moss JR, McPhee AJ, Jeffries WS, et al. (2005) Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med 352: 2477–2486.
31. Tieu J, Crowther CA, Middleton P (2009) Dietary advice in pregnancy for preventing gestational diabetes mellitus. Cochrane Database of Systematic Reviews; 3:
32. Oostdam N, van Poppel MN, Eekhoff EM, Wouters MG, van Mechelen W (2009) Design of FitFor2 study: the effects of an exercise program on insulin sensitivity and plasma glucose levels in pregnant women at high risk for gestational diabetes. BMC Pregnancy and Childbirth 9: 1.
33. Chasan-Taber L, Marcus BH, Staned E, Ciccolo JT, Marquez DX, et al. (2009) A randomized controlled trial of prenatal physical activity to prevent gestational diabetes: design and methods. J Women's Health 18: 851–859.
Is the Subject Area "Physical activity" applicable to this article?
Is the Subject Area "Diet" applicable to this article?
Is the Subject Area "Pregnancy" applicable to this article?
Is the Subject Area "Neonates" applicable to this article?
Is the Subject Area "Weight gain" applicable to this article?
Medical risk factors
Is the Subject Area "Medical risk factors" applicable to this article?
Is the Subject Area "Gestational diabetes" applicable to this article?
Is the Subject Area "Insulin" applicable to this article?


Pakistan Tehreek-i-Insaf pledged that once in government, it will carry out sweeping reforms for the country's welfare. As the government takes the reins, Dawn.com will be monitoring progress on major promises from the 2018 election manifesto, as well as any important pledges made in the course of its term.
The promises picked for tracking are specific and tangible, and were thus preferred over more broad and abstract ones, where progress cannot be gauged accurately.
This page will be updated by Dawn.com across the government's entire tenure.
Please visit the ABOUT section to understand methodology.
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text:
Governor Palin's Alaska Homecoming
RUSH: To the audio sound bites. This is funny. The Drive-Bys hated waiting for Sarah Palin to arrive in Alaska. We've got David Rodham Gergen here with Anderson Cooper. Cooper says, 'It's going to be interesting, David, to hear Sarah Palin in a different context. This is a state where the people know her, where clearly she's overwhelmingly popular. She's not going to be telling them about the bridge to nowhere, and thanks but no thanks.'
GERGEN: I'm rubbing my eyes in disbelief that we're all sitting here waiting to watch the arrival of a vice presidential candidate. I mean, we don't do this for presidential candidates.
RUSH: Yeah, well, why do you think this is happening, David Rodham Gergen? Then Cooper says, 'Well, David Gergen, as you watch this, can this last? I mean, it's been a honeymoon period for Sarah Palin. Can it go on much longer?'
GERGEN: It's unimaginable to me; it's unbelievable to me that we're sitting here at 11:30 at night Eastern Standard Time.
RUSH: Why? This is just great. It's unbelievable to me we're sitting here at 11:30 at night Eastern Standard Time waiting for this woman to arrive. Well, why don't you go home?
RUSH: Sarah Palin, huge ovation last night when she got home to Fairbanks, Alaska. We have three sound bites.
PALIN: This is just overwhelming. Thank you. Oh, I am so glad to get to be here. Thank you for being here, Fairbanks, thank you for letting us be here. Oh, this is beautiful. Thank you. Wow, it's been an amazing couple of weeks, and I just want to thank you, Alaska, for your support and for your encouragement and what we've been doing is taking our campaign on the road of course across the nation, and we've been carrying our message of reform to the American people, and we've been talking all about Alaska, and people are — (cheers and applause) What a trip it's been, and I cannot wait until you meet John McCain. He's a friend of Alaska, and he's going to be the next president of the United States of America.
RUSH: They love her up there. They literally love her up there. She's got 80% approval ratings, higher than that, even, as governor in Alaska. She's genuine here. She's very authentic, real person. You can hear that she genuinely appreciates this outpouring of support. Here's the next bite.
PALIN: Americans know that you've done some great work up here, Alaskans, as we've kind of taken the government here in the state, put it back on the side of the people in these last couple of years. You've really helped shake things up. Just like we're going to go to the Washington, DC, to do also is shake things up in the capital. What John McCain has noticed is that Alaska has returned to the fundamental truth that government is not always the answer. In fact, government, too often, is the problem. So we've gone back to the basics and we put government back on the side of the people.
RUSH: There's a little channeling of Ronald Reagan there, Ronaldus Magnus, 'government is the problem' is one of his most famous utterances. Here's the third sound bite from Governor Palin.
PALIN: I feel like I'm preaching to the choir because you guys already know this. It's a message for America. We've got a reform agenda for America. That's what we're going to run on here, guys, and I am so honored, and I am so humbled to serve as Senator McCain's running mate, and I am equally honored and forever will be honored to serve as your governor of the great state of Alaska. Representing our fellow Alaskans is not only a tremendous honor, it's also a sacred duty. And you have placed great faith in me. And as I travel across the country, I will keep that faith by fulfilling my duty to you and spreading our good message, and I promise that I will do my best to make Alaskans proud in the weeks to come, and I would ask you to help me, then, let us work together, let us elect John McCain, a great man who will be a great president because he's a friend of Alaska, and he will be our next president.
RUSH: Governor Palin, by the way, today was impugned and insulted by no less than Lincoln Chafee, who has the same number of brain cells as an amoeba. Senator Chafee, ex-Senator Chafee called her a cocky wacko. We now know why he's an ex-senator. The guy is an order of fries short of a Happy Meal on a given day, and that's the best he does. Let's just keep it coming. All you moderate, liberal Republican, Democrat, just keep it coming, just keep leveling these mindless insults. Now, as you listen to Governor Palin, as you listen to her, as you are mesmerized by her ability speak, I don't know if she's on a prompter there or not, but you hear how genuine she is, she's excited and all that, compare it to, say, this.
BIDEN: Uh, uh, Chuck Graham, state senator, is here. Stand up, Chuck. Let 'em see you. (rimshot) Oh, God love you. What am I talking about? (rimshot) I tell you what, you're making everybody else stand up, though, pal. (rimshot) I tell you what, stand up for Chuck. (rimshot)
RUSH: Stand up for Chuck! Hey, Chuck, stand up over there. Oh, my God, what am I — oh, stand up for Chuck. And then of course there was this yesterday.
BIDEN: Hillary Clinton is as qualified or more qualified than I am to be vice president of the United States of America. (rimshot) Let's get that straight. She's a truly close personal friend. (rimshot) She is qualified to be president of the United States of America. (rimshot) She's easily qualified to be vice president of the United States of America. (rimshot) And, quite frankly, um, it might have been a better pick than me. (rimshot) But she's first rate.
RUSH: So there you have Joe Biden essentially saying he's not the guy for the job.

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My new book Gardening Under Lights: The Complete Guide for Indoor Growers is here! You can order it NOW on Amazon in hardback or Kindle, or, order personalized signed copies from me at my web shop (click Shop tab above).
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text:
Q: Neural net from floating point to interger weights I've made a simple program that uses a neural network with floating point weights in C. Now I want to use int8_t or int16_t weights, how should I change the code? The training is a problematic part with integers.
Here is the simple example:
This part is the net definition
#include <stdio.h>
#include <stdlib.h>

typedef double NNType;
// numer of inputs
#define IN 2
// number neurons layer hidden
#define HID 8
// numer of outputs
#define OUT 1
// learning constant
#define EPS 0.1

NNType input[IN]; // input
NNType hidden[HID]; // layer hidden
NNType output[OUT]; // output
NNType weightH[HID][IN]; // weights layer hidden
NNType biasesH[HID]; // biases layer hidden
NNType weightO[OUT][HID]; // weights output
NNType biasesO[OUT]; // biases output

This part is the network calculation and the training part
inline NNType Activation(NNType x)
{
   return x>0?x:0;
}

inline NNType Derivative(NNType x)
{
   return x>0?1:0;
}

NNType NetworkResult(NNType inp1,NNType inp2)
{
   // load the inputs
   input[0]=inp1;
   input[1]=inp2;
   // compute hidden layer
   for (int i=0;i<HID;i++)
   {
      hidden[i]=biasesH[i];
      for (int j=0;j<IN;j++)
         hidden[i] += input[j]*weightH[i][j];
      hidden[i]=Activation(hidden[i]);
   }
   // compute output
   for (int i=0;i<OUT;i++)
   {
      output[i]=biasesO[i];
      for (int j=0;j<HID;j++)
         output[i] += hidden[j]*weightO[i][j];
      output[i]=Activation(output[i]);
   }
   return output[0];
}

void TrainNet(NNType inp1,NNType inp2,NNType result)
{
   NetworkResult(inp1,inp2);
   NNType DeltaO[OUT];
   NNType DeltaH[HID];
   // layer output
   NNType err= result-output[0];
   DeltaO[0]=err*Derivative(output[0]);
   // layer hidden
   for (int i=0;i<HID;i++)
   {
      NNType err=0;
      for (int j=0;j<OUT;j++)
         err+= DeltaO[j]*weightO[j][i];
      DeltaH[i]=err*Derivative(hidden[i]);
   }
   // change weights
   // layer output
   for (int i=0;i<OUT;i++)
   {
      for (int j=0;j<HID;j++)
         weightO[i][j]+=EPS*DeltaO[i]*hidden[j];
      biasesO[i]+=EPS*DeltaO[i];
   }
   // layer hidden
   for (int i=0;i<HID;i++)
   {
      for (int j=0;j<IN;j++)
         weightH[i][j]+=EPS*DeltaH[i]*input[j];
      biasesH[i]+=EPS*DeltaH[i];
   }
}

This is the main of the program that trains the net to learn an xor operation
// constant for weights initializations
#define CONSTINIT 0.1

int main(int argc, char *argv[])
{
   srand(1);
   // initalize weights and biases
   for (int i=0;i<HID;i++)
   {
      for (int j=0;j<IN;j++)
         weightH[i][j]= 2.0 * ( (rand()/((NNType)RAND_MAX)) - 0.5 ) * CONSTINIT;
      biasesH[i]=0.1;
   }
   for (int i=0;i<OUT;i++)
   {
      for (int j=0;j<HID;j++)
         weightO[i][j]= 2.0 * ( (rand()/((NNType)RAND_MAX)) - 0.5 ) * CONSTINIT;
      biasesO[i]=0.1;
   }
   // calculate the results with the random weights
   printf("0 0 = %f\n",NetworkResult(0,0));
   printf("0 1 = %f\n",NetworkResult(0,1));
   printf("1 0 = %f\n",NetworkResult(1,0));
   printf("1 1 = %f\n",NetworkResult(1,1));
   printf("\n");
   // Train the net to recognize an xor operation
   for (int i=0;i<1000;i++)
   {
      TrainNet(0,0,0); // input 0 0 result 0
      TrainNet(0,1,1); // input 0 1 result 1
      TrainNet(1,0,1); // input 1 0 result 1
      TrainNet(1,1,0); // input 1 1 result 0
   }
   // calculate the results after the train
   printf("0 0 = %f\n",NetworkResult(0,0));
   printf("0 1 = %f\n",NetworkResult(0,1));
   printf("1 0 = %f\n",NetworkResult(1,0));
   printf("1 1 = %f\n",NetworkResult(1,1));
   printf("\n");
   return 0;
}

A:
I've made a simple program that uses a neural network with floating point weights in C. Now I want to use int8_t or int16_t weights, how should I change the code? The training is a problematic part with integers.

I do not understand why the training would be problematic and I think you've meant that it is problematic with floats.
Anyways, what I would like to suggest is that you do not use integers over floating points for your neural network operation. You see, by the nature of mathematical operations performed during using or training the network it must be implemented using floats (or doubles). Otherwise you would loose information from  the fractional part.
Of course, using integers is possible. After all a float x.yy is going to be an integer when multiplied by 100 but it would be an overkill to implement as everything would have to be shifted this way.

A:
Now I want to use int8_t or int16_t weights, how should I change the code? The training is a problematic part with integers.

Code uses floating point to keep values in the range of [-1.0 ... 1.0].
Moving directly to integer types only gives 3 values -1,0,1.  With integers,  I'd expect you would want to use a scaling.  With int8_t, maybe [-64...64].  Each time code uses *, the product needs to be scaled.
// input[j] * weightH[i][j]
input[j] * weightH[i][j] / 64;

Select addition/subtraction need tests to detect overflow.

What looks easy with floating point, becomes tricky (although maybe faster) with integers.
Some untested code for just the random number part.
// weightH[i][j]= 2.0 * ( (rand()/((NNType)RAND_MAX)) - 0.5 ) * CONSTINIT;

// Break CONSTINIT into even numerator/denominator parts.
// Map [0...RAND_MAX] to [-64 ... 64]* CONSTINIT
#define scale_up (2LL*(64 - -64 + 1)*CONSTINIT_NUMERATOR)
#define scale_dn (2LL*RAND_MAX*CONSTINIT_DENOMINATOR)
long long r = scale_up*rand() - scale_up*RAND_MAX/2;
// add proper signed one-half divisor
r += (r < 0) ? -scale_dn/2 : scale_dn/2;
weightH[i][j]= r/scale_dn;  // scale down

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text:
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Australian organic standards group yet to be finalised
By Neil Merrett
01-Apr-2007 - Last updated on 19-Jul-2008 at 17:57 GMT
Related tags: Organic food
An Australian standards body working to establish a committee to
rule on organic certification for domestic and imported food
products has denied media reports suggesting that it has finalised
representatives for the group.
With talks over the standards set to begin in May, the denial is likely to prove a setback for organic federation of Australia (OFA), which called for the standards to be imposed in a bid to drive growth in organic food production. Standards Australia told AP-Foodtechnology.com that contrary to claims made last week, it was still waiting to confirm representation from "a couple" of the 16 food organisations invited to make up the committee. Organic food and beverage products are becoming an increasingly important stream of revenue for processors in the country, due to consumer concerns with the quality of non-organic and GM ingredients. The OFA's Andre Leu, believes that the implementation of the national standards will ensure consumer faith in organic products, by acting as a basis for domestic regulation in the country. A similar standard is already in place for the country's exports of organic food, and the OFA is keen that domestic market for organic foods is finally following suite. "It was the Australian Government that proposed that an Australian Standard was the correct way to get domestic regulation," Leu told AP-Foodtechnology.com. "It took a lot of consultation and investigation before we decided that this was the only option." He added that the standards, which would be used by the industry to define organic production techniques, allowable inputs and prohibited practices, could conceivably be in place by the end of the year. The OFA has already begun discussions with the government over the possibility of enforcing the standard to ensure organic food production is fully protected in the country. Australia is becoming an increasingly important player in the burgeoning global organic food market. The OFA estimates that Australia currently ranks behind only Japan and China in the Asia Pacific region for supply and demand of the goods. In findings published last year by the Rural Industries Research and Development Corporation (RIRDC), the popularity of organic food was found to have increased significantly. The research found organic food to be one of the fastest growing sectors in the global food industry, growing at double-digit rates compared to just 1-2 per cent on average in other foods. The report added that Australia could have a strong role to play in meeting this growth. "Australia's competitiveness in cereals and pulses will allow it to be competitive in baked products, noodles and pasta," it stated.
Related topics: Policy, Oceania, Industry growth
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Asia's organic food industry coming of age
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Webinar Healthy Ageing: Mobility & Cognitive Health
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Economic enormity: Format innovation key to getting APAC plant-based product costs down
Riding the Fourth Wave: NO HARM DONE's eco-friendly coffee capsules blending tradition with innovation
Safety First: Australia poppy seed poisoning recalls, Top 10 APAC food safety stories in 2022, kimchi spot checks and more feature in our round-up
'Sold deceptively': Indian regulator warns against plant-based ghee, butter products carrying 'dairy terms'
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COVID-19 and APAC's food and beverage sector: All our coronavirus news...in one place
Food & Beverage Trailblazers
FoodNavigator-Asia
Expert advisory panel


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NHTI's Business Training Center
Drone Education Training
Introduction to Pix4D
with SkyOp Certified Instructor
Monday February 6, Wednesday February 8, and Friday February 10, 2023 from 10:00am - 3:30pm ET
SkyOp Online Classroom
In this course you will learn best practices for drone-based image data collection. You will also get an introduction to basic post-processing techniques using Pix4Dmapper. You will need to have access to the current version of Pix4Dmapper so you can work on class activities.
The instruction is being provided by SkyOp, the leading sUAS courseware developer and training company in the country. The course will focus on small Unmanned Aircraft Systems (sUAS). These are defined by the FAA as weighing less than 55 lbs.
Session 1: Feb 6 - 10th, 2023
Mon, Wed, and Fri from 10:00 am - 3:30 pm
Only 5 days left to register!
For more info, call us at (603) 230-4022
(603) 230-4022 • 31 College Drive, Concord, NH 03301 (get directions) • nhtibtc@ccsnh.edu • © 2023
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The German Kulmhof Death Camp in Chelmno operated over two periods: between 1941 and 1943, and between 1944 and 1945. The Museum of the former camp was founded in 1990 as a branch of the District Museum in Konin. It features several exhibitions and offers educational activities. Its main mission is to commemorate the fate of the Jews exterminated in Kulmhof Camp.


With the festive season underway, Trading Standards in Derby are reminding residents of the dangers posed by unsafe fireworks and sparklers by urging them to be vigilant against illegal sales.
Fireworks must now have a CE mark and should have clear instructions and warnings in English.
Only shops with the correct license can sell fireworks. It is illegal to sell them from mobile stalls, such as market stalls or from the back of a van and they should not be sold through social media.
Fireworks should be stored out of the reach of children and animals in damp free areas away from flammable materials, including petrol, oil or paint.
Trading Standards will be visiting premises selling fireworks in Derby to make sure their products are correctly stored, that their stock meets safety standards and that sellers are aware that they must not sell fireworks to under 18s.
"We will be inspecting premises to make sure that fireworks are being stored safely and legally. Fireworks are a form of explosive and pose a significant risk if stored or used incorrectly.
To report a shop or dealer selling fireworks illegally or to under 18s, residents should contact the Citizens Advice Consumer Service on 03454 04 05 06.


How Far is Universal Mesmerizing Woods?
"Mesmerizing Woods" is a farm house plots project with a gated community concept. Located at village Jawal, near Hinjewadi - the IT Hub of Pune and Pirangut – a fast developing suburb of Pune, Mesmerizing Woods is located amidst these two hot spots.
The project promises most exotic flavor to your life. As the name indicates, Mesmerizing Woods, gives you an enchanting experience of being delightfully close to nature. Soft rustle of leaves, spiced up by gentle breeze wafting sweet natural aroma, cool-serene shadows of trees guarantee stimulating experience of rich biodiversity. This sprawling project, covering an area of about 175 acres is tastefully developed landscape with beautifully contoured land. Nature thrives here blissfully exhibiting rich flora & fauna.
Universal Landmarks is one of the most reputed and reliable names in land acquisition, development & creating plots for individual use. Established in the year 2013, Universal Landmarks is a team of dedicated professionals who have prolific experience in Land acquisition, land development, plotting, construction and real estate. These professionals, who in their individual capacity have enjoyed a highly successful career in their respective lives, have developed more than 3000 acres of land in a span of over two decades. With a passion to make the dream of owning land property come true for thousands of people, these professionals have joined hands to work seamlessly and relentlessly as a team for Universal Landmarks, giving best of their experience, expertise & energy to create the most reputed brand name: UNIVERSAL LANDMARKS.
In a short span of time, the brand Universal Landmarks has earned respect, reliability and confidence of hundreds of individual plot owners, who have purchased our developed plots. The emergence of Universal Landmarks has facilitated exciting investment options for number of customers.
We have established the unique culture of trust & transparency. For us, land development means going beyond customer's expectations and creating a blissful world on the premises. Land development involves building of internal roads, providing water & electricity facility for individual plot owners, building pavements / walkways, illumination of internal roads, public places, creating resting zones, security surveillance points, gardens – plantation & amusement park. Creating environment friendly properties with optimum use of solar energy & natural resources is our prime endeavour.
We invest, not only in terms of money, but we invest our ideas, energies and innovative thoughts to make a delightful living on every single plot. Today, Universal Landmarks has lot of land development projects on hand, aggregating over 2000 acres at number of scenic places around Pune & parts of Konkan in Maharashtra.


text:
Q: iOS 11 largetitle bar tint color cannot be set I having a problem in restoring back the bartint color for iOS 11 large title after had set the navigationbar to transparent.
Reproduction step:

*

*Set the navigation bar background image and shadow to empty
UIImage().

*The navigation bar became transparent.

*Set the navigation bar background image and shadow to nil and set back the bar tint color.

*The large title navigation bar became white color; if scroll
down(the old navigation bar present) then you can see the bar tint
color only applied to old style navigation bar.

Tried:
*Set the navigation background color and status color to the bar tint color, yes it changed but without translucent visual effect like we set bar tint color.
Does anyone has face the same problem as me and able to fix it with any solution or workaround ?
Original

After went through a page with transparent navigation and come back

FYI, I also apply custom navigation controller to set back from transparent to default color,
class CustomNavigationController: UINavigationController {

override func viewDidLoad() {
    super.viewDidLoad()

    // Do any additional setup after loading the view.
}

override func didReceiveMemoryWarning() {
    super.didReceiveMemoryWarning()
    // Dispose of any resources that can be recreated.
}

override func pushViewController(_ viewController: UIViewController, animated: Bool) {

    super.pushViewController(viewController, animated: animated)
   self.setDefaultNavigationBar()

}

override func popViewController(animated: Bool) -> UIViewController? {
    self.setDefaultNavigationBar()
    return super.popViewController(animated: animated)

}

override func popToViewController(_ viewController: UIViewController, animated: Bool) -> [UIViewController]? {
    self.setDefaultNavigationBar()
    return super.popToViewController(viewController, animated: animated)

}

override func popToRootViewController(animated: Bool) -> [UIViewController]? {
    self.setDefaultNavigationBar()
    return super.popToRootViewController(animated: animated)
}

func setDefaultNavigationBar() {

    let navigationBarColor = UIColor(hexString: "#00b5baff")!
    self.navigationBar.setBackgroundImage(nil, for: .default)
    self.navigationBar.shadowImage = nil
    //self.navigationController?.navigationBar.backgroundColor = UIColor.clear
    //self.navigationController?.navigationBar.tintColor = UIColor.clear
    self.navigationBar.barTintColor = navigationBarColor

}

/*
// MARK: - Navigation

// In a storyboard-based application, you will often want to do a little preparation before navigation
override func prepare(for segue: UIStoryboardSegue, sender: Any?) {
    // Get the new view controller using segue.destinationViewController.
    // Pass the selected object to the new view controller.
}
*/

}

A: Try providing transparent.png image as background image to achieve the transparency. That should work. If that doesn't work try using below code to just update the large title colors.
self.navigationController?.navigationBar.largeTitleTextAttributes =
[NSAttributedStringKey.foregroundColor: UIColor.blue,
 NSAttributedStringKey.font: UIFont(name: fontName, size: 30) ??
                             UIFont.systemFont(ofSize: 30)]

Hope this helps!

A: Not sure if this will help anyone, but this is what worked for me when the navigation background tint became white after selecting 'Prefers Large Titles' :
    let appearance = UINavigationBarAppearance()
    appearance.backgroundColor = FlatBlue()
    appearance.titleTextAttributes = [NSAttributedString.Key.foregroundColor : UIColor.white]
    navigationBar.standardAppearance = appearance
    navigationBar.scrollEdgeAppearance = appearance


UK – India Week. Building Winning Partnerships.
UK-India Week sets the pace for the two global nations' bold, winning partnership, showcasing the potential for collaboration between the two markets. Its cornerstone event is the India Inc. Leaders' Summit, a two-day exchange of enterprise, innovation and opportunity which convenes international business leaders, change-makers and entrepreneurs to enhance collaboration.
India Inc. is a London-based media house that produces incisive content and events on investment, trade and policy matters relating to India's increasingly globalised economic and strategic agenda. Its flagship publication is the fortnightly 'India Global Business'. In addition, India Inc. also organises several high impact events, the latest being UK-India Week 2019.


text:
A nontoxic glue for plywood – from glucose, citric acid
FOR IMMEDIATE RELEASE | May 11, 2022
"A Fully Bio-Based Adhesive from Glucose and Citric Acid for Plywood with High-Performance"
ACS Applied Materials & Interfaces
The go-to materials for building home furniture, décor and floors are composite wood products that come in large sheets. But the glues and resins holding together particleboard, fiberboard and plywood usually contain formaldehyde and could release this probable carcinogen into the air. To develop a nontoxic adhesive, researchers reporting in ACS Applied Materials & Interfaces have combined glucose and citric acid — sugar and an orange juice ingredient — into a strong, water-resistant wood glue for plywood.
To make plywood, manufacturers glue together thin layers of wood and then cure the material under pressure and heat, creating large, flexible panels. One of the most common adhesives is a urea-formaldehyde resin because it's inexpensive and bonds strongly to wood. However, formaldehyde emissions from plywood with this type of resin have raised health and environmental concerns. Previous studies have shown that solutions of sucrose, a two-unit sugar made of glucose and fructose, and citric acid form a natural and water-resistant wood glue. But a zinc chloride catalyst is required to decrease the energy consumption for the plywood curing, which also reduces the adhesive's strength. So, Hong Lei and colleagues wanted to see if pure glucose and citric acid could produce a strong adhesive with a less energy-intensive curing process.
The researchers heated solutions of glucose and varying amounts of citric acid into a sticky liquid that they applied onto poplar veneers. Then they stacked three veneers and pressed them into a single sheet at 392 F for six minutes. The team cut the sheets into smaller pieces for strength tests and found that under pressures greater than 101 psi, the plywood samples all broke along the wood fibers and not at the glued seams. These results satisfy the standard requirement for plywood in China. When the plywood samples were soaked in hot or boiling water, only the ones made with citric acid to glucose ratios above 0.6 had adhesive strengths that satisfied the standard requirement. The researchers attribute these results to the increase in ester links between citric acid and wood, which increased the wood-binding strength and water-resistance. Citric acid-glucose adhesives hold promise for the wood products industry, the researchers say.
The authors acknowledge funding from the National Natural Science Foundation of China, the Yunnan Provincial Natural Science Foundation, the 111 project and the French National Research Agency (ANR).
Citric acid and glucose produce a wood glue that creates strong, water-resistant three-layer plywood.
Credit: Adapted from ACS Applied Materials & Interfaces 2022, DOI: 10.1021/acsami.2c02859


text:
Victoria woman Kaela Mehl is expected to plead guilty to second-degree murder in a retrial for the murder of her 18-month-old daughter Charlotte Cunningham, who died in September 2015. (Black Press Media file photo)
Guilty plea expected in retrial for Victoria mom accused in toddler's death
Kaela Mehl successfully appealed her first-degree murder charge last year
Jake Romphf
The woman accused of killing her 18-month-old daughter intends to plead guilty in her upcoming retrial.
Kaela Mehl was convicted of first-degree murder in the 2015 death of her daughter, Charlotte Cunningham, in October 2017. She was sentenced to life in prison with no chance of parole for 25 years.
Mehl appealed the conviction, arguing that trial counsel failed to provide reasonable professional assistance and that one of the jurors was biased. Her appeal stated that throughout the trial one juror made gestures of support or sympathy towards the family of her daughter's father.
In June 2021, the Court of Appeal ruled in her favour, overruling Mehl's conviction and ordering a new trial.
Mehl was scheduled to appear in a Victoria courtroom on Monday (Nov. 14) and was expected to enter a guilty plea, but the case was adjourned to a later date. However, her lawyer on Monday said that Mehl still intends to plead guilty to second-degree murder, a spokesperson for the prosecution service told Black Press Media.
The Victoria woman pleaded not guilty to the first-degree murder charge in her original trial.
ALSO READ: Retrial date set for Victoria woman accused of killing toddler daughter
Do you have a story tip? Email: newsroom@vicnews.com.
kaela mehlVictoria
'Freedom Convoy' did not pose threat to the security of Canada: CSIS director
New Democrats call for independent review of government's COVID-19 response


text: git test for iOS1505

redpajama_set_name: RedPajamaGithub


text:
Q: select max between two columns in linq i have dateSend Column and dateEdit Column in product table, i can select max dateSend with this code:
(from pro in Products.ToList()
select new { pro.DateSend }).Max();

but i have max between dateSend and dateEdit, please help me.

A: (from pro in Products.ToList()
let max = Max(pro.DateSend, pro.DateEdit)
select max).Max()

static DateTime? Max(DateTime? a, DateTime? b)
{
    if (!a.HasValue && !b.HasValue) return a;  // doesn't matter

    if (!a.HasValue) return b;
    if (!b.HasValue) return a;

    return a.Value > b.Value ? a : b;
}

A: If you're not opposed to ditching the query syntax it's simpler to do:
DateTime max = Products.Max(p=>p.DateSend > p.DateEdit ? p.DateSend : p.DateEdit);

A: ((from pro in Products.ToList()
select pro.DateSend).Union(
from pro2 in Products.ToList()
select pro.DateEdit
)).Max();

A: Same code but with One LinQ
   (From pro in Products.ToList
    Let max = {pro.DateSend, pro.DateEdit}.Max
    select max).Max

If pro items not a valid DateTime, It will crash or return unexpected result.
Other solution(Parsing the Products list items):
 (From pro in Products.ToList
    Let DSend as DateTime = Convert.ToDateTime(Iif(ValidDateTime(pro.DateSend), pro.DateSend, DateTime.MinValue))
    Let DEdit as DateTime = Convert.ToDateTime(Iif(ValidDateTime(pro.DateEdit), pro.DateEdit, DateTime.MinValue))
    Let MaxDate as DateTime= {DSend, DEdit}.Max
    select MaxDate).Max

private function ValidDateTime(ByVal Dat as Object) as Boolean
   if Dat Is Nothing OrElse IsDbNull(Dat) OrElse String.IsNullOrEmpty(Dat)  then
      return false
   end if

   return true
end function

You can replace the ValidDateTime with an "Iif".
Other example returning max value of Double items, but in the personalized object(MyObject), items are String type.
  (From Item as MyObject in MyListOfObject
    Let Frec as Double = Convert.ToDouble(Iif(String.IsNullOrEmpty(Item.Frecuency),0,Item.Frecuency))
    Let Pot as Double = Convert.ToDouble(Iif(String.IsNullOrEmpty(Item.Power),0,Item.Power))
    Let max as Double= {Frec, Pot}.Max
    select max).Max

Recap

*

*Declare Column Items separately. Parse It(If you need)

*Create an Item for store the max value of the row(all columns)

*Create an Array, put in all declared Items and asign array to the before declared item(Item created in step 2)

*Append in the end of the array the Max property like this: {Item1, Item2,...}.Max

*Create Select fr return the Max item

*Append in the end the linq Max property. (MyLinQ).Max

I hope this code helps to someone.
Sorry for my English.


Hello all, long time no see!
I posted my last walk in 2014. After that, I walked elsewhere.
The walk from my home to Rome in 2015, changed something: I no longer preferred the illusion of wilderness, but had learned to appreciate rural areas, city centers and even the 'in between' zone of industrial estates, shopping centers and apartment blocks.
So when in 2018, my love for the Highlands begged to be rekindled, I looked for a mix of rough and inhabited.
April 17, I arrived on Barra. A walk north to Harris seemed to fit my idea of a balanced walk.
To set the scene: I saw an eagle within half an hour after departure from Castlebay.
I crossed sunny Barra via the Virgin and the Child, the summit of Heabhal, a chambered cairn and a dun. My route touched the Hebridean Way and crossed over to Loch an Duin, where it was windy and un-campsite-looking. In Thiarabhagh, a pleasant looking village and harbor, I walked over to the Hotel, looking for a meal, but didn't like the look of it and walked back, soon accompanied by a family of four. He worked at the airport, she was in childcare business. Friendly people, relaxed. After a life on the mainland, they had settled on Barra, where they were born. They advised me to find a camping spot beyond the airport. Too far out for my taste. When I saw a wooded hillside a mile up the road, I camped on a flat spot between trees higher up.
Two nuns boarding the Twin Otter to Barra, one blaming the other "you do not pay me enough for this!"
Craignish Point and Garbh Reisa.
In the morning, I caught the ferry over to Eriskay. The sea looked choppy, but the crossing was alright, with great views all around. I climbed Ben Scrien, a nice little hill, hardly mentioned in any guidebook, but characterful and well worth the climb. Very windy on the summit. In the village shop I bought a snack and crossed the causeway to South Uist. I followed various paths along the coastline north. At an aisled house at 733203 my route turned inland, aiming for the Coop at Daliburgh, a well sorted shop. Walking along the road to Lochboisdale was quite boring, and quite wet lateron. With some 2 miles to go a driver relieved me of the drudgery and drove me to the pier.
Near a farm called Lasgair I crossed the river northward to connect to a track to the foot of Triuirebhein. At a water work, a group of concrete basins, I tried to pitch the tent. The first spot was too windy, but I cooked dinner at least, the second spot was on the lee side of a basin, but still too windy, and the last attempt was without tent in just a flysheet bivouac. In the meantime, it had started to rain. When rain and wind picked up a notch, I decided to walk back out and wished I had paid more attention to navigation on the way in. I arrived at the Lochboisdale Hotel around 11pm. Hot bath, hot chocolate and a good night sleep would recuperate me nicely..
After the rains, the weather felt clear and fresh. I retraced my path to the water intake and on to the foot of Triuirebheinn. The terrain could not be called solid ground in any way. I took my time climbing the hill. On the connecting ridge northward, the walking was much better, drier underfoot. Since I did not plot a route, and just decided to find my way, I was surprised by very steep heathery steps on the way down, which called for a lot of weaving in and out.
In the Bealach a'Chaolais lies a Souterrain. I could see it had been a nice spot to live in. Warm, less windy than elsewhere.
Stulabhal is a nice hill. From the south, one climbs onto a small plateau with two lochans, with an attractive buttress right above them. You climb a broad gully, and come out on the summit. Great views, at only 384m.
The way down was across curved gneiss banks, like a pod of whales. I had a good lunch on the shores of Loch Snigiscleit. To reach Loch Ainort, I needed to climb Beinn Aleinn almost to the top, and cross no man's land to the shores of the sea loch, which was to be rounded clockwise. A long way on asphalt, I kept myself entertained by looking at the farms and houses and the materials/mess around them. On the north shore of the loch the houses get quainter, until you reach an arboretum, a tree garden. Meanwhile, low tide turned the narrow loch into a labyrinth of skerries with oystercatchers flying on and off to try and pry shellfish from between the kelp.
I pitched the tent in full view of Beinn Mhòr. The summit became visible, and the mountain bathed in sunshine for the rest of the afternoon. I could not be seduced to climb it though.
Stulaval trig point, looking north to Beinn Mhòr, South Uist.
I departed after the early morning drizzle ended. Higher up, I picked up a path, which would lead me to the Bealach Crosgaird, I was sure. Naturally, this confidence was not based on navigational rigour, or so I found out on a bealach more than one kilometer to the south, near Beinn na Tobha.
No visibility, so the climb up to Beinn Mhòr was not too pleasant. A trig point can improve such a mood, because of the locational certainty it gives, but in this case also because this particular one looks very good, made from local stone. After this, I followed the ridge north. When the mist swirled the right way, I could see that the summit of the hill is perched above a steep drop.
I skipped Beinn Choradail, meandered through a labyrinth of rocky outcrops on the way to the foot of Hecla and had a good look down Gleann Uisinis, looking very wild. Originally I had planned to camp there, but this didn't fit my other plans. Coming down the north side of Hecla, the views opened up: blindingly bright in browns and blues after the previous clag, the cliffs of Skye in the distance.
Crossing the floodgate at NF814402, Hecla at the horizon.
Hearty breakfast & good conversations got me underway along the coastline and across the causeway to the shop at Creagorry. I was on Benbecula now, the flattest island. My route took a turn north through Torlum and Griminis. There, a faint track is shown to cross the moss to Baile na Cailleach, but the Cicerone guide I read discourages its use and my eyes gave me the evidence. It might be on the map, but it is a ribbon of water so no, it is not fit for walking, I concluded. I rounded the coast to the bay of Culla, a nice beach with lots of birds. I ate my locally produced hot-smoked salmon and called home.
On top of dykes of big round stones I reached Balivanich. Now I like my villages and towns 'real' even when it involves 'ugly' to ensure authenticity (yes, a snobby tourist's reasoning ), but this town is beyond charming ugliness, and so this tourist just visited the supermarket and decided to take a look at the timetable in a bus stop. It was 3pm, at 3.02 a bus across the causeway to North Uist appeared. Therefore, I landed on North Uist at 3.15. Hurray for opportunism . I followed the road eastward to Cladach Chairinis, hoping for a nice camping spot on farmland. No-one to be seen, so I ended up in a ruined sheiling on the peninsula of Calternis.
Rain passed by in the night. I waited for it to subside and left at 10.30. I could see the foot of the hill, so took my time climbing it, slow enough for the views to have appeared when I arrived on the summit at one.
In my humble opinion Eaval is the best hill of this trip . Its setting, its shape and in particular its views are grand. The view towards the sea is across a patchwork of lochans and rocky banks. Benbecula shows its likeness to a drenched and worn fiber kitchen cloth and on the southern horizon sit Hecla and Beinn Mhor, whose summits never ever were without cloud since my day 3 camp. A puzzle can be played comparing view and map: say if a loch is salt or fresh.
I descended the hill eastward, to find a natural arch in the cliffs at 926606. The walking on the cliff tops is fine. Dry underfoot, with the dark sea and the white foam, the petrels, the short grass. I lunched near the arch to watch the swell hit the rocks.
My route turned northwest towards Burabhal. I met two islanders and their Belgian friend near its summit, who questioned my sanity (or praised my attitude) for being on this hill. They were regulars.
The walk to the head of Loch Euphort is long, since this sealoch cuts Uist almost in two. Rain set in halfway. I visited a stone circle, just to distract, and reprimanded myself for postponing finding a place to camp. One of the tricks of wild camping in inhabited areas is to find the right mood to go and ask for water and permission. Eventually, I rang a doorbell and asked if the derelict harbor building on the pier would be a convenient spot. Inside a roofless building I pitched, only to find out the grass was underlaid by concrete. I repitched outside for a windy night.
This day I remember as one of many miles of walking along the A865. On these islands, a bike is the best transport, followed by a kayak. Walking across the land one will resort to use of the main roads, sooner or later. Fortunately, there's not very many cars on them.
I walked on to the Bayhead shop where a shop assistant got me coffee from the machine. I crossed Balranald, an RSPB-reserve. Not many birds here, but in general I've seen a lot, mostly snipe. A farmer, turning the ground, stopped his tractor for a chat when he saw me taking pictures of his work. He reminded me of my granddad, who was an expert with tractor and plough, me sitting on the fender of the tractor, next to him, long ago.
I walked along a wide beach and visited a headland (Gearraidh Gall) with another natural arch. Here, petrels soar above the cliffs, dropping down to the waves to gain speed, only to return to same apex again and again. The flying petrels watched the raven, who tried to find out whether there's eggs underneath the sitting petrels, operating in a sly manner.
Upon returning to the A865 I fantasized that history would repeat itself and I would bump into a bus stand minutes before the bus arrived. There was no bus, the road is long and undulating, and it started to rain rather continuously. I looked over my shoulder to see cars coming (I could see miles of road) but a) no-one came and b) those who drove by didn't pick me up and c) those who tried (a BMW Z4 roadster) discovered I wanted to go the other way. But d) an American pensioner in a rental car had all the time of the world to bring me to the Berneray Causeway, chatting all the while . I had planned to camp, but the Gatliff Trust hostel was warm, dry, cheap and I would have a room to myself. Ian and Dorothy, Glaswegian cyclists, provided good company. I hope I did, too.
I woke to sunshine and blue skies at 6. Before the ferry to Harris, I wanted to have walked round the island, so I ate and packed quickly and was on my way at 7. Very pleasant walk to the road end, and then up Beinn Sleibhe and anti-clockwise down the west coast. Fabulous beaches, windy seas, dark skies, stunning views across to Harris. The south-west side of Berneray is where dunes fade into machair and meadowland beautifully, and across the stony beach of Loch Buirgh I made the ferry with 15 minutes to spare.
Peat was harvested near Loch Langavat, where I turned straight north into the wild of Harris. The walk in was enjoyable, especially when a sea eagle came to circle me. I video-ed it, but soon felt like an intruder and moved on. After that I got tired, and couldn't find a place to camp in the usual type of terrain: none of the grassy patches in river bends were dry enough, no ridges were still enough, and no plateau was flat enough. I ended up on a heathery promontory, the tent pitched so skewed and crooked, the inside was shaped like a beach chair. The place is called Loch Dubh Màs Holasmul, doesn't it sound like a desert?
The South harris interior is not seen as being of any interest to hillwalkers, not a single line is written about it in my SMC guide. But try the satellite view and you'll see: these hills are rough. They were in the path of glaciers many times, hence the elephant skin look. Try climbing them and you'll notice the lack of any logic in the terrain, and when you stand on a summit and look across to the next hill, you'll notice the hills are covered as thin as possible by soil and vegetation, rock jutting through the tattered skin everywhere. Many false summits too. Heileasbhal Mor, An Coileach (with a curious notch in its skyline between the high point and the trig point) and Ceann Reamhar na Sroine are quite a handful. A feast for lovers of empty, pathless terrain. To finish it off, an exciting gully in the cliffs of Creag nan Eòin lands one on the path through Bealach Eòrabhat, a good track (coffin road?) to Luskentyre. Some heavy showers rolled in so I took a longish break on the doorstep of a white shed/house where the Abhainn Lacasdail joins the sands.
My route turns north-east across Ceann Reamhar and down to Tarbert. Again, not many suitable camping spots, so I walked into Tarbert. The hotels were woefully expensive, but the fish'n'chips were quite good and the backpackers Hostel was kinda perfect, with the company of two Americans of the intrepid kind. One was a guide in Denali National Park, the other planning to write a book about Beaujolais. I dried the gear for the journey home and took the bus to Stornoway in the morning.
Looking south from Heileasbhal Mòr, Roineabhal top right.
The route on the map was reconstructed from my gpx-files, using less waypoints.
Long, straight bits are ferry crossings and in one place a lift in a car or a short bus-ride.
The metres of ascent recorded here are calculated by the WH map, but please be reminded any route on these islands is winding, with a great many ups and downs just because of all those tussocks, hillocks, lochans and stream beds.
In 2019, in a few weeks, I'll be visiting Islay, Jura and possibly Colonsay. Looking forward to it, I love islands!
Ideal day out: A longish walk through a wooded glen, camping high up, climbing a hill in the evening and returning to the tent to cook.